kg_agent/visualization/knowledge_search_traverse/debug_component.jsx

import React, { useState, useCallback, useMemo, useEffect } from 'react';
import { createRoot } from 'react-dom/client';
import {
  ReactFlow,
  Controls,
  Background,
  useNodesState,
  useEdgesState,
  Handle,
  Position,
  useReactFlow,
  ReactFlowProvider,
} from '@xyflow/react';
import '@xyflow/react/dist/style.css';

const data = {
  "nodes": {
    "root_o": {
      "type": "root",
      "query": "如何制作反映人类双标行为的猫咪表情包梗图",
      "level": 0,
      "relevance_score": 1,
      "strategy": "原始问题",
      "iteration": 0,
      "is_selected": true
    },
    "round_0": {
      "type": "round",
      "query": "Round 0 (初始化)",
      "level": 0,
      "relevance_score": 0,
      "strategy": "初始化",
      "iteration": 0,
      "is_selected": true
    },
    "step_seg_r0": {
      "type": "step",
      "query": "步骤1: 分段 (4个segment)",
      "level": 1,
      "relevance_score": 0,
      "strategy": "分段",
      "iteration": 0,
      "is_selected": true
    },
    "segment_0_r0": {
      "type": "segment",
      "query": "[疑问引导] 如何",
      "level": 2,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"如何\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“如何”本身不包含任何动作意图，无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为的猫咪表情包梗图）的方法，而词条“如何”是一个高度通用的疑问词，不包含任何具体品类信息。根据评估原则，通用概念不等于特定概念，因此品类匹配度极低。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "疑问引导",
      "iteration": 0,
      "is_selected": true,
      "segment_type": "疑问引导",
      "domain_index": 0,
      "domain_type": "疑问引导"
    },
    "word_如何_seg0_0": {
      "type": "word",
      "query": "如何",
      "level": 3,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"如何\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“如何”本身不包含任何动作意图，无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为的猫咪表情包梗图）的方法，而词条“如何”是一个高度通用的疑问词，不包含任何具体品类信息。根据评估原则，通用概念不等于特定概念，因此品类匹配度极低。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "segment_1_r0": {
      "type": "segment",
      "query": "[核心动作] 制作",
      "level": 2,
      "relevance_score": 0.71,
      "evaluationReason": "【评估对象】词条\"制作\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.98】词条“制作”与原始问题中的核心动作“制作”完全一致，是原始问题动作的精确匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为的猫咪表情包梗图）的方法，而词条“制作”是一个非常通用的动词，没有包含任何品类信息，属于过度泛化。通用概念不等于特定概念，因此品类匹配度极低。\n【最终得分 0.71】\n【规则说明】规则A：动机高分保护生效（动机0.98≥0.8），实际得分0.71已≥0.7",
      "strategy": "核心动作",
      "iteration": 0,
      "is_selected": true,
      "segment_type": "核心动作",
      "domain_index": 1,
      "domain_type": "核心动作"
    },
    "word_制作_seg1_0": {
      "type": "word",
      "query": "制作",
      "level": 3,
      "relevance_score": 0.71,
      "evaluationReason": "【评估对象】词条\"制作\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.98】词条“制作”与原始问题中的核心动作“制作”完全一致，是原始问题动作的精确匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为的猫咪表情包梗图）的方法，而词条“制作”是一个非常通用的动词，没有包含任何品类信息，属于过度泛化。通用概念不等于特定概念，因此品类匹配度极低。\n【最终得分 0.71】\n【规则说明】规则A：动机高分保护生效（动机0.98≥0.8），实际得分0.71已≥0.7",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "segment_2_r0": {
      "type": "segment",
      "query": "[修饰短语] 反映人类双标行为的",
      "level": 2,
      "relevance_score": 0.09,
      "evaluationReason": "【评估对象】词条\"反映人类双标行为的\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“反映人类双标行为的”是一个描述性短语，没有明确的动作意图，无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.30】词条'反映人类双标行为的'是原始问题中的一个限定词，但缺少核心主体'猫咪表情包梗图'，因此匹配度较低。\n【最终得分 0.09】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.09已≤0.5",
      "strategy": "修饰短语",
      "iteration": 0,
      "is_selected": true,
      "segment_type": "修饰短语",
      "domain_index": 2,
      "domain_type": "修饰短语"
    },
    "word_反映_seg2_0": {
      "type": "word",
      "query": "反映",
      "level": 3,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"反映\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”，而词条“反映”虽然是原始问题中的一个动词，但它不是核心动机，且词条本身无法构成一个完整的动作意图，因此动机维度得分为0。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为的猫咪表情包梗图）的品类，而词条“反映”是一个通用动词，不包含任何品类信息，属于过度泛化，因此品类匹配度极低。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "word_人类_seg2_1": {
      "type": "word",
      "query": "人类",
      "level": 3,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"人类\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“人类”是一个名词，没有明确的动作意图，无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为）的猫咪表情包梗图，而词条“人类”是一个高度泛化的概念，虽然原始问题中包含“人类”一词，但词条本身没有提供任何关于“双标行为”、“猫咪表情包”或“梗图制作”的特定信息，属于通用概念与特定概念的匹配，因此得分较低。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "word_双标_seg2_2": {
      "type": "word",
      "query": "双标",
      "level": 3,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"双标\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“双标”是一个名词，没有明确的动作意图，因此无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为）的特定形式（猫咪表情包梗图），而词条“双标”是一个通用概念，虽然是原始问题中的一个限定词，但词条本身没有包含原始问题的主体和限定词，属于过度泛化。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "word_行为_seg2_3": {
      "type": "word",
      "query": "行为",
      "level": 3,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"行为\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“行为”是一个名词，没有明确的动作意图，无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为）的特定形式（猫咪表情包梗图）的指南，而词条“行为”是一个非常通用的概念，没有限定词，无法与原始问题的特定品类匹配，属于过度泛化。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "segment_3_r0": {
      "type": "segment",
      "query": "[中心名词] 猫咪表情包梗图",
      "level": 2,
      "relevance_score": 0.23399999999999999,
      "evaluationReason": "【评估对象】词条\"猫咪表情包梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“猫咪表情包梗图”是一个名词短语，没有明确的动作意图，因此无法与原始问题的“制作”动作进行匹配。\n【品类维度 0.78】词条'猫咪表情包梗图'与原始问题中的核心主体'猫咪表情包梗图'完全匹配，但缺少了限定词'反映人类双标行为的'，因此给予较高正向分数。\n【最终得分 0.23】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.23已≤0.5",
      "strategy": "中心名词",
      "iteration": 0,
      "is_selected": true,
      "segment_type": "中心名词",
      "domain_index": 3,
      "domain_type": "中心名词"
    },
    "word_猫咪_seg3_0": {
      "type": "word",
      "query": "猫咪",
      "level": 3,
      "relevance_score": 0.09,
      "evaluationReason": "【评估对象】词条\"猫咪\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“猫咪”是一个名词，没有明确的动作意图，无法与原始问题的“制作”动作进行匹配。\n【品类维度 0.30】原始问题的主体是'猫咪表情包梗图'，词条是'猫咪'。词条包含了原始问题核心主体的一部分，但缺少了'表情包梗图'这个关键限定词，且原始问题中的'猫咪'是作为表情包的主体，而词条'猫咪'是泛指，语义身份存在差异。\n【最终得分 0.09】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.09已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "word_表情包_seg3_1": {
      "type": "word",
      "query": "表情包",
      "level": 3,
      "relevance_score": 0.15,
      "evaluationReason": "【评估对象】词条\"表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”，而词条“表情包”是一个名词，没有明确的动作意图，因此无法评估动作匹配度。\n【品类维度 0.50】词条“表情包”是原始问题“猫咪表情包梗图”的核心主体，但缺少了“猫咪”、“梗图”等限定词，属于核心主体匹配但限定词缺失。\n【最终得分 0.15】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.15已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "word_梗图_seg3_2": {
      "type": "word",
      "query": "梗图",
      "level": 3,
      "relevance_score": 0.024,
      "evaluationReason": "【评估对象】词条\"梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】词条“梗图”是一个名词，没有明确的动作意图，因此无法与原始问题的核心动机“制作”进行匹配。\n【品类维度 0.08】原始问题是关于制作特定主题（人类双标行为）和特定形式（猫咪表情包梗图）的梗图，而词条“梗图”是一个非常通用的概念，没有包含原始问题中的任何限定词（人类双标行为、猫咪表情包）。通用概念不等于特定概念，因此品类匹配度低。\n【最终得分 0.02】\n【规则说明】规则B：动机低分限制生效（动机0.00≤0.2），实际得分0.02已≤0.5",
      "strategy": "Word",
      "iteration": 0,
      "is_selected": true
    },
    "round_1": {
      "type": "round",
      "query": "Round 1",
      "level": 10,
      "relevance_score": 0,
      "strategy": "第1轮",
      "iteration": 1,
      "is_selected": true
    },
    "step_sug_r1": {
      "type": "step",
      "query": "步骤1: 请求&评估推荐词 (90个)",
      "level": 11,
      "relevance_score": 0,
      "strategy": "请求&评估推荐词",
      "iteration": 1,
      "is_selected": true
    },
    "q_如何_r1_0": {
      "type": "q",
      "query": "[Q] 如何",
      "level": 12,
      "relevance_score": 0.024,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 0,
      "domain_type": "疑问引导"
    },
    "sug_如何快速减肥_r1_q0_0": {
      "type": "sug",
      "query": "[SUG] 如何快速减肥",
      "level": 13,
      "relevance_score": -0.53,
      "evaluationReason": "【评估对象】词条\"如何快速减肥\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 -0.50】原始问题动机为“制作”，sug词条动机为“减肥”。两者动作意图完全不相关，且制作与减肥的方向也存在明显的冲突。\n【品类维度 -0.55】原始问题核心是“人类双标行为的猫咪表情包梗图”，涉及到“猫咪”、“表情包”、“梗图”，而sug词条是“如何快速减肥”，二者品类完全不相关，对象完全错位。\n【延伸词维度 -0.60】sug词条「快速减肥」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题、对象、目的上完全不相关，引入了与原始问题核心需求无关的全新主题，严重稀释了原始问题的聚焦度，属于作用域稀释型延伸词。\n【最终得分 -0.53】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何培养男人主动给你花钱_r1_q0_1": {
      "type": "sug",
      "query": "[SUG] 如何培养男人主动给你花钱",
      "level": 13,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"如何培养男人主动给你花钱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.80】原始问题的核心动机是「制作」反映特定主题的表情包梗图。sug词条的核心动机是「培养」。两者在动作意图上完全不相关，且方向大相径庭，一个侧重创作，一个侧重影响或改变他人的行为。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。Sug词条对象层为「男人」的「花钱行为」，两者话题品类完全不同，对象层与场景层均不匹配，存在负向偏离。\n【延伸词维度 -0.60】sug词条与原始问题完全不相关，原始问题是关于制作猫咪表情包梗图，而sug词条是关于培养男人花钱，两者在主题、目的和内容上都毫无关联，属于作用域稀释型，且稀释程度极高。\n【最终得分 -0.80】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何快速挣到钱_r1_q0_2": {
      "type": "sug",
      "query": "[SUG] 如何快速挣到钱",
      "level": 13,
      "relevance_score": -0.4,
      "evaluationReason": "【评估对象】词条\"如何快速挣到钱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题是「制作表情包梗图」，sug词条是「挣钱」。两者在动机维度完全不匹配。\n【品类维度 -0.85】原始问题涉及“猫咪表情包梗图”和“人类双标行为”的创作主题，sug词条“如何快速挣到钱”的主体是金钱获取方式。两者内容主体完全无关，且品类冲突。\n【延伸词维度 -0.60】sug词条「如何快速挣到钱」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、目的和内容上完全不相关，引入了与原始问题核心需求无关的全新主题，严重稀释了原始问题的聚焦度，属于作用域稀释型延伸词。\n【最终得分 -0.40】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何和女生聊天找话题_r1_q0_3": {
      "type": "sug",
      "query": "[SUG] 如何和女生聊天找话题",
      "level": 13,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"如何和女生聊天找话题\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.00】原始问题的核心动机是学习「制作」表情包/梗图，而sug词条的动机是学习「聊天/找话题」。两者动机完全不匹配。\n【品类维度 -0.80】原始问题内容主体为《人类双标行为的猫咪表情包梗图》，sug词条内容主体为《和女生聊天找话题》。两者核心对象和场景完全不匹配，是完全不同领域的类别。\n【延伸词维度 -0.60】sug词条「如何和女生聊天找话题」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、目的和对象上完全不相关，属于作用域稀释型，且偏离度极高。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何快速入睡_r1_q0_4": {
      "type": "sug",
      "query": "[SUG] 如何快速入睡",
      "level": 13,
      "relevance_score": -0.78,
      "evaluationReason": "【评估对象】词条\"如何快速入睡\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图，表达特定主题\n【动机维度 -0.80】原始问题的核心动机是「制作」具有特定意义的「表情包梗图」，而sug词条的动机是「入睡」。两者动作意图完全不相关，且方向相反，一个是主动创造，另一个是被动状态。\n【品类维度 -0.80】原始问题内容主体为《人类双标行为的猫咪表情包梗图制作》，sug词条内容主体为《入睡》的方法。两者核心对象和场景完全不匹配，品类差异巨大，语义错位。\n【延伸词维度 -0.60】sug词条「如何快速入睡」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、目的和内容上完全不相关，属于作用域稀释型，且偏离度极高。\n【最终得分 -0.78】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何让男生持续上头_r1_q0_5": {
      "type": "sug",
      "query": "[SUG] 如何让男生持续上头",
      "level": 13,
      "relevance_score": -0.4,
      "evaluationReason": "【评估对象】词条\"如何让男生持续上头\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包/梗图，而sug词条的动机是「让」男生如何，两者动作意图完全不相关，方向不同，因此得分为0。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。Sug词条对象层为「男生」，缺失全部核心对象和场景，类别完全冲突，为负向偏离。\n【延伸词维度 -0.60】sug词条与原始问题完全无关，原始问题是关于制作表情包梗图，而sug词条是关于两性情感，两者在主题、目的和内容上均无任何关联，属于作用域稀释型，且稀释程度非常高。\n【最终得分 -0.40】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何逼自己自律学习_r1_q0_6": {
      "type": "sug",
      "query": "[SUG] 如何逼自己自律学习",
      "level": 13,
      "relevance_score": -0.4,
      "evaluationReason": "【评估对象】词条\"如何逼自己自律学习\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题的核心动机是「制作」表情包，而sug词条的核心动机是「逼」自己学习。两者动作意图完全不匹配。\n【品类维度 -0.85】原始问题主题集中在“猫咪表情包梗图”这一创作内容，sug词条“如何逼自己自律学习”与原始问题的主体内容（猫、表情包、梗图）完全不符，属于完全不同的品类，且没有可关联的限定词。\n【延伸词维度 -0.60】sug词条「如何逼自己自律学习」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、目的和对象上完全不相关，引入了与原始问题核心需求相悖的全新主题，严重稀释了原始问题的聚焦度，导致负面影响。\n【最终得分 -0.40】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何连接别人家的加密wifi_r1_q0_7": {
      "type": "sug",
      "query": "[SUG] 如何连接别人家的加密wifi",
      "level": 13,
      "relevance_score": -0.4,
      "evaluationReason": "【评估对象】词条\"如何连接别人家的加密wifi\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图，sug词条是「连接」别人家的加密wifi，两者动作意图完全不相关。\n【品类维度 -0.85】原始问题涉及“猫咪表情包梗图”这一创作类内容主体，且有具体行为“双标”限定。sug词条为“如何连接别人家的加密wifi”这一计算机网络类内容，二者品类完全不符，且限定词也无关联，属于完全负向的偏离。\n【延伸词维度 -0.60】sug词条「如何连接别人家的加密wifi」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、目的和内容上完全不相关，引入了与原始问题核心需求无关的全新主题，严重稀释了原始问题的聚焦度，导致负面影响。\n【最终得分 -0.40】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何养好头发_r1_q0_8": {
      "type": "sug",
      "query": "[SUG] 如何养好头发",
      "level": 13,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"如何养好头发\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 -0.80】原始问题的核心动机是「制作」反映特定主题的表情包梗图。sug词条的动机是「养好」头发。两者之间没有任何关联性和相似性，属于完全不相关的动作意图。\n【品类维度 -0.85】原始问题对象层为「人类双标行为的猫咪表情包梗图」，限定词为「反映/制作」，场景层无。 Sug词条对象层为「头发」，限定词为「养好」。两者在对象层和限定词上完全不匹配，品类冲突，属于负向偏离。\n【延伸词维度 -0.60】sug词条「如何养好头发」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」完全不相关，引入了与原始问题核心目的和作用域完全无关的全新主题，严重稀释了原始问题的聚焦度，导致内容偏离，属于作用域稀释型。\n【最终得分 -0.80】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_如何治疗早泻时间短_r1_q0_9": {
      "type": "sug",
      "query": "[SUG] 如何治疗早泻时间短",
      "level": 13,
      "relevance_score": -0.46,
      "evaluationReason": "【评估对象】词条\"如何治疗早泻时间短\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/制作梗图\n【动机维度 0.00】原始问题的核心动机是「制作」，sug词条的核心动机是「治疗」。两者动作意图完全无关。\n【品类维度 -1.00】原始问题涉及「猫咪表情包梗图」这一创意内容制作领域，sug词条「如何治疗早泻时间短」属于医疗健康领域，两者在内容主体上完全不相关，且领域冲突，评分为最低。\n【延伸词维度 -0.60】sug词条「如何治疗早泻时间短」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、目的、对象和场景上完全不相关，引入了与原始问题完全无关的医学健康领域内容，严重稀释了原始问题的聚焦度，导致内容偏离，属于作用域稀释型延伸词。\n【最终得分 -0.46】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "q_制作_r1_1": {
      "type": "q",
      "query": "[Q] 制作",
      "level": 12,
      "relevance_score": 0.71,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 1,
      "domain_type": "核心动作"
    },
    "sug_制作ppt_r1_q1_0": {
      "type": "sug",
      "query": "[SUG] 制作ppt",
      "level": 13,
      "relevance_score": -0.1600000000000001,
      "evaluationReason": "【评估对象】词条\"制作ppt\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。\n【动机维度 0.35】原始问题的动机是「制作」表情包梗图，sug词条的动机也是「制作」ppt。两者核心动作均为「制作」，属于同一大类，动作方向有间接关联，但制作的对象（表情包梗图 vs ppt）完全不同，因此属于弱相关。\n【品类维度 -0.80】原始问题核心是「猫咪表情包梗图」，涉及「人类双标行为」这一限定。而sug词条「制作ppt」内容主体完全偏离，与原始问题无任何关联，属于品类错位。\n【延伸词维度 -0.15】sug词条「制作ppt」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和对象完全不符，引入了无关的工具和主题，严重稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.16】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作表情包_r1_q1_1": {
      "type": "sug",
      "query": "[SUG] 制作表情包",
      "level": 13,
      "relevance_score": 0.815,
      "evaluationReason": "【评估对象】词条\"制作表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.95】原始问题的核心动机是「制作」，sug词条「制作表情包」的核心动机也是「制作」。sug词条的动作意图和原始问题完全一致。\n【品类维度 0.50】原始问题对象层为“猫咪表情包梗图”，限定词有“反映人类双标行为”；sug词对象层为“表情包”，是原始问题的泛化对象层，但缺少所有的限定词，故给予中等匹配分。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。sug词条是原始问题核心动作的概括，不构成延伸。\n【最终得分 0.81】\n【规则说明】情况4：无延伸词，权重调整为 动机70% + 品类30%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.71
    },
    "sug_制作冰糖葫芦_r1_q1_2": {
      "type": "sug",
      "query": "[SUG] 制作冰糖葫芦",
      "level": 13,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"制作冰糖葫芦\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 -0.80】原始问题核心动机是“制作”，sug词条「制作冰糖葫芦」中也包含“制作”的动作。但制作表情包梗图和制作冰糖葫芦是完全不同的制作方向和目的，动机上完全不相关。\n【品类维度 -0.85】原始问题涉及「猫咪表情包梗图」、「双标行为」内容，而sug词条是「制作冰糖葫芦」，两者在对象层和场景层均完全不匹配，是完全不同品类的内容，因此评为负分。\n【延伸词维度 -0.60】sug词条「制作冰糖葫芦」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题和目的上完全不相关，引入了与原始问题核心需求无关的全新概念，严重稀释了原始问题的聚焦度，属于作用域稀释型，且程度较深。\n【最终得分 -0.80】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作ppt的ai软件_r1_q1_3": {
      "type": "sug",
      "query": "[SUG] 制作ppt的ai软件",
      "level": 13,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"制作ppt的ai软件\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”，sug词条「制作ppt的ai软件」的核心动机也是“制作”。尽管两者都涉及“制作”，但制作的对象完全不同，sug词条无法帮助原始问题的「制作表情包」行为，因此动机匹配度为0。\n【品类维度 -0.80】原始问题问的是「人类双标行为」「猫咪表情包梗图」的「制作」方法，sug词条是「制作ppt的ai软件」，二者在对象层和场景层完全不匹配，品类冲突。\n【延伸词维度 -0.60】sug词条「制作ppt的ai软件」中的所有词汇，如「制作」、「ppt」、「ai」、「软件」，均与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的作用域（制作、猫咪表情包梗图、人类双标行为）完全不符，引入了全新的、不相关的概念，严重稀释了原始问题的聚焦度，导致内容完全偏离，属于作用域稀释型延伸词。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作视频_r1_q1_4": {
      "type": "sug",
      "query": "[SUG] 制作视频",
      "level": 13,
      "relevance_score": -0.09500000000000001,
      "evaluationReason": "【评估对象】词条\"制作视频\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题核心动机是“制作”，平台sug词条核心动机也是“制作”，但在对象上存在差异。原始问题是制作「表情包梗图」，sug词条是制作「视频」。虽然都是『制作』，但『表情包』和『视频』是两个完全不同的事物，无法形成直接的上下属或并列关系，故无法形成高相关的动机匹配，但又不能完全否定。\n【品类维度 -0.20】原始问题是关于“猫咪表情包梗图”，sug词条是“制作视频”，核心对象类型完全不匹配，一个需要图片素材，一个需要视频素材，存在品类错位。\n【延伸词维度 -0.15】原始问题是制作「表情包梗图」，而sug词条是「制作视频」。视频与表情包梗图是两种不同的内容形式，引入「视频」稀释了原始问题对「表情包梗图」的聚焦度，降低了内容的针对性，属于作用域稀释型。\n【最终得分 -0.10】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作美食_r1_q1_5": {
      "type": "sug",
      "query": "[SUG] 制作美食",
      "level": 13,
      "relevance_score": -0.6800000000000002,
      "evaluationReason": "【评估对象】词条\"制作美食\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.60】原始问题的核心动机是“制作”（表情包梗图），sug词条的核心动机是“制作”（美食），两者动作相同但制作的对象和场景完全不同，动机意图方向明显偏离。\n【品类维度 -0.80】原始问题核心对象为「猫咪表情包梗图」，sug词条核心对象为「美食」。两者对象完全不相关，品类冲突，属于负向偏离。\n【延伸词维度 -0.60】sug词条「制作美食」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在动机、对象、场景上均不相关，属于完全无关的延伸，严重稀释了原始问题的核心意图。\n【最终得分 -0.68】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作简历_r1_q1_6": {
      "type": "sug",
      "query": "[SUG] 制作简历",
      "level": 13,
      "relevance_score": -0.6800000000000002,
      "evaluationReason": "【评估对象】词条\"制作简历\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 -0.60】原始问题核心动机是「制作」反映人类双标行为的猫咪表情包梗图，sug词条核心动机是「制作」简历。虽然两者都有「制作」动作，但sug词条提供的「制作简历」和原始问题「制作梗图」在具体行为和目的上完全不相关。\n【品类维度 -0.80】原始问题对象层为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条对象层为「简历」，二者对象层完全不匹配，品类冲突严重，功能等方面属于完全不同领域。\n【延伸词维度 -0.60】sug词条「制作简历」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题、对象和目的上完全不相关，引入了与原始问题核心需求无关的全新主题，严重稀释了原始问题的聚焦度，属于作用域稀释型，且程度较深。\n【最终得分 -0.68】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作饮品_r1_q1_7": {
      "type": "sug",
      "query": "[SUG] 制作饮品",
      "level": 13,
      "relevance_score": -0.6600000000000001,
      "evaluationReason": "【评估对象】词条\"制作饮品\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.80】原始问题的核心动机是“制作”（表情包梗图），sug词条的动机是“制作”（饮品），两者均有制作行为，但动作对象完全不同，导致制作行为偏离很大。\n【品类维度 -0.50】原始问题核心是《表现人类双标行为的猫咪表情包梗图》，sug词是《饮品》，对象层完全不同，且无任何场景限定词匹配。客体类别完全偏离，负向抵消了动作的关联性。\n【延伸词维度 -0.60】sug词条「制作饮品」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在对象和目的上完全不相关，引入了与原始问题核心需求相悖的全新主题，严重稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.66】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作小房子_r1_q1_8": {
      "type": "sug",
      "query": "[SUG] 制作小房子",
      "level": 13,
      "relevance_score": -0.20500000000000007,
      "evaluationReason": "【评估对象】词条\"制作小房子\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.35】原始问题核心动机是“制作”，sug词条核心动机也是“制作”，两者动作意图相同，但制作的对象完全不同，属于动作相关。\n【品类维度 -0.80】原始问题内容主体为《猫咪表情包梗图》，包含对象层「梗图、表情包」及场景层「猫咪、双标行为」。Sug词条《制作小房子》主体为「小房子」，与原始问题完全不匹配，品类完全无关。\n【延伸词维度 -0.60】sug词条「制作小房子」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题、对象和目的上完全不相关，引入了与原始问题核心需求无关的全新概念，严重稀释了原始问题的聚焦度，导致内容偏离，属于作用域稀释型延伸词。\n【最终得分 -0.21】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "sug_制作表格_r1_q1_9": {
      "type": "sug",
      "query": "[SUG] 制作表格",
      "level": 13,
      "relevance_score": -0.5650000000000001,
      "evaluationReason": "【评估对象】词条\"制作表格\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 -0.70】原始问题的核心动机是围绕生成内容进行创作，旨在「制作」出一种特定形式的表情包梗图。sug词条「制作表格」虽然包含「制作」这一动词，但其指向的是「表格」的制作，与原始问题的「表情包梗图」的制作在行为目的和内容产出上存在显著差异，属于完全不同的制作行为，动作意图完全不匹配且方向相反。\n【品类维度 -0.50】原始问题核心对象是「表情包梗图」，场景是「人类双标行为」和「猫咪」。Sug词条核心对象为「表格」，品类完全不匹配，完全不同维度的内容主体。\n【延伸词维度 -0.15】sug词条「制作表格」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关主题，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.57】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.71
    },
    "q_反映_r1_2": {
      "type": "q",
      "query": "[Q] 反映",
      "level": 12,
      "relevance_score": 0.024,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 2,
      "domain_type": "修饰短语"
    },
    "sug_反映问题还是反应问题_r1_q2_0": {
      "type": "sug",
      "query": "[SUG] 反映问题还是反应问题",
      "level": 13,
      "relevance_score": -0.7600000000000001,
      "evaluationReason": "【评估对象】词条\"反映问题还是反应问题\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「反映问题还是反应问题」关注的是词语用法选择，没有明确的动作意图。\n【品类维度 -0.80】原始问题的核心是「猫咪表情包梗图」这一核心对象，限定词为「人类双标行为」。sug词为抽象的语法辨析「反映问题还是反应问题」，两者对象和限定词完全不匹配，品类冲突严重。\n【延伸词维度 -0.60】sug词条「反映问题还是反应问题」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」完全无关，属于作用域无关型，且严重稀释了原始问题的核心意图，导致负向评分。\n【最终得分 -0.76】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映和反应的区别_r1_q2_1": {
      "type": "sug",
      "query": "[SUG] 反映和反应的区别",
      "level": 13,
      "relevance_score": -0.35500000000000004,
      "evaluationReason": "【评估对象】词条\"反映和反应的区别\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」，sug词条「反映和反应的区别」的核心动机是「辨析/理解」。两者动作完全不匹配。\n【品类维度 -0.85】原始问题主要涉及“猫咪表情包梗图”的制作，而sug词条是关于“反映和反应的区别”的语言知识。两者内容主体完全不相关，品类冲突严重，评分极低。\n【延伸词维度 -0.15】sug词条「反映和反应的区别」与原始问题「制作猫咪表情包梗图」的核心目的和作用域完全无关，属于无关型延伸词，且分散了用户注意力，稀释了原始问题的聚焦度。\n【最终得分 -0.36】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映是什么意思_r1_q2_2": {
      "type": "sug",
      "query": "[SUG] 反映是什么意思",
      "level": 13,
      "relevance_score": -0.04,
      "evaluationReason": "【评估对象】词条\"反映是什么意思\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 -0.05】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「反映是什么意思」的核心动机是「获取或解释」某种含义，二者动作方向不同。\n【品类维度 0.00】原始问题内容主体为《人类双标行为的猫咪表情包梗图》，sug词条内容主体为《反映》，二者无任何内容主体的关联性，属于不同品类，因此得分为0分0分处理。\n【延伸词维度 -0.15】sug词条「反映是什么意思」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关的词义解释，严重稀释了原始问题的聚焦度。\n【最终得分 -0.04】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映者_r1_q2_3": {
      "type": "sug",
      "query": "[SUG] 反映者",
      "level": 13,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"反映者\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】sug词条「反映者」是纯名词，不包含任何动作意图，因此无法与原始问题的「制作」动机进行匹配。\n【品类维度 0.05】sug词是抽象的动词转名词，原始问题是一个具体的制作行为，两者相距甚远。sug词过度泛化，几乎无法体现原始问题中任何内容主体。\n【延伸词维度 -0.15】sug词条「反映者」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心需求完全不符，引入了无关概念，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反应力小游戏_r1_q2_4": {
      "type": "sug",
      "query": "[SUG] 反应力小游戏",
      "level": 13,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"反应力小游戏\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是“制作”梗图，而sug词条「反应力小游戏」的动作意图是“玩”/“进行”小游戏，两者动作意图完全不匹配。\n【品类维度 -0.80】原始问题核心对象是《猫咪表情包梗图》，场景是《人类双标行为》。sug词条核心对象是《小游戏》，场景是《反应力》。两者品类完全不相关，且词语含义偏离度大。\n【延伸词维度 -0.60】原始问题是关于“制作猫咪表情包梗图”的，核心是“制作”和“表情包梗图”；sug词条“反应力小游戏”与原始问题的“制作”和“表情包梗图”完全不相关，引入了全新的、不相关的概念，严重稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反应蛋白高是什么意思_r1_q2_5": {
      "type": "sug",
      "query": "[SUG] 反应蛋白高是什么意思",
      "level": 13,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"反应蛋白高是什么意思\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「反应蛋白高是什么意思」的意图是「理解/获取知识」。两者动机完全不匹配。\n【品类维度 -0.80】原始问题是关于“猫咪表情包梗图”的制作，涉及娱乐创作领域。sug词条是“反应蛋白高是什么意思”，属于医学健康领域。两者内容主体完全不匹配，品类冲突，完全风马牛不相及。\n【延伸词维度 -0.60】sug词条「反应蛋白高是什么意思」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、内容和目的上完全不相关。sug词条引入了与原始问题制作表情包梗图毫无关联的医学概念，严重稀释了原始问题的聚焦度，导致内容完全偏离，属于作用域稀释型。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映拼音_r1_q2_6": {
      "type": "sug",
      "query": "[SUG] 反映拼音",
      "level": 13,
      "relevance_score": -0.7100000000000001,
      "evaluationReason": "【评估对象】词条\"反映拼音\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，sug词条「反映拼音」无任何动作意图，因此无法匹配。\n【品类维度 -0.85】原始问题是关于《猫咪表情包梗图》的制作方法，限定词有《双标行为》，核心对象是《猫咪表情包梗图》。sug词条《反映拼音》与原始问题核心主体及所有限定词完全不符，品类严重冲突。\n【延伸词维度 -0.15】sug词条「反映拼音」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关信息，严重稀释了原始问题的聚焦度。\n【最终得分 -0.71】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映财务状况的会计要素_r1_q2_7": {
      "type": "sug",
      "query": "[SUG] 反映财务状况的会计要素",
      "level": 13,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"反映财务状况的会计要素\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包或梗图，而sug词条“反映财务状况的会计要素”中没有明确的动作意图。sug词条缺失动机层，无法与原始问题的动机进行匹配。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「会计要素」，场景层为「反映财务状况」。两者对象层和场景层完全不匹配，品类完全冲突，负相关。\n【延伸词维度 -0.60】sug词条中的“财务状况”和“会计要素”与原始问题中的“人类双标行为”和“猫咪表情包梗图”完全不相关，引入了与原始问题核心主题无关的全新概念，严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.80】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映的英语_r1_q2_8": {
      "type": "sug",
      "query": "[SUG] 反映的英语",
      "level": 13,
      "relevance_score": -0.3,
      "evaluationReason": "【评估对象】词条\"反映的英语\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包/梗图，而sug词条「反映的英语」是指查询“反映”这个词的英文翻译，两者动作意图完全不相关。\n【品类维度 -0.60】原始问题意在制作「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条「反映的英语」与原始问题在对象和场景上均完全错位，品类差异巨大。\n【延伸词维度 -0.60】sug词条「反映的英语」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关的语言学习主题，严重稀释了原始问题的聚焦度，属于作用域稀释型延伸词。\n【最终得分 -0.30】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_反映事物间的互补关系_r1_q2_9": {
      "type": "sug",
      "query": "[SUG] 反映事物间的互补关系",
      "level": 13,
      "relevance_score": -0.26,
      "evaluationReason": "【评估对象】词条\"反映事物间的互补关系\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，sug词表示「反映」互补关系。两者在行为意图上完全不一致，没有关联。sug词条的重点在于概念的「反映」，与原始问题的「制作」行为毫无关联。\n【品类维度 -0.50】原始问题的核心主体是「猫咪表情包梗图」及「双标行为」；sug词条「反映事物间的互补关系」与原始问题主体品类完全错位，无任何关联。\n【延伸词维度 -0.60】sug词条「反映事物间的互补关系」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题、对象、目的上完全不相关，引入了全新的、不相干的概念，严重稀释了原始问题的聚焦度，导致内容偏离，属于作用域稀释型。\n【最终得分 -0.26】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "q_人类_r1_3": {
      "type": "q",
      "query": "[Q] 人类",
      "level": 12,
      "relevance_score": 0.024,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 2,
      "domain_type": "修饰短语"
    },
    "sug_人类一败涂地_r1_q3_0": {
      "type": "sug",
      "query": "[SUG] 人类一败涂地",
      "level": 13,
      "relevance_score": -0.6700000000000002,
      "evaluationReason": "【评估对象】词条\"人类一败涂地\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】sug词条「人类一败涂地」是游戏名称，不包含任何动作意图，所以不存在动机匹配度。\n【品类维度 -0.80】原始问题核心是“猫咪表情包梗图”，限定词为“双标行为”。sug词条“人类一败涂地”与原始问题在对象层、场景层均不匹配，品类完全冲突。\n【延伸词维度 -0.15】sug词条「人类一败涂地」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，属于无关且稀释原始问题聚焦度的延伸，降低了内容的针对性。\n【最终得分 -0.67】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类狗窝_r1_q3_1": {
      "type": "sug",
      "query": "[SUG] 人类狗窝",
      "level": 13,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"人类狗窝\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”猫咪表情包梗图，而sug词条“人类狗窝”是一个名词性短语，无法识别出任何动作意图，因此无法评估动机匹配度。\n【品类维度 -0.20】原始问题主对象是“猫咪表情包梗图”，限定词是“双标行为”。sug词《人类狗窝》是完全不相关的名词概念，无论是主体还是限定词都完全没有关联性极低且有误导性。\n【延伸词维度 -0.15】sug词条「人类狗窝」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心概念和目的完全不符。它既不属于原始问题的任何作用域，也无法促进原始目的的达成，反而引入了无关且可能分散注意力的信息，属于作用域稀释型。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类幼崽陪伴指南_r1_q3_2": {
      "type": "sug",
      "query": "[SUG] 人类幼崽陪伴指南",
      "level": 13,
      "relevance_score": -0.52,
      "evaluationReason": "【评估对象】词条\"人类幼崽陪伴指南\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意在制作表情包，sug词条「人类幼崽陪伴指南」不含任何动作意图，且内容方向完全不匹配，因此动机维度评分为0。\n【品类维度 -0.50】原始问题核心是“猫咪表情包梗图”和“人类双标行为”，sug词条是“人类幼崽陪伴指南”，二者在主体对象上完全不匹配，品类冲突。\n【延伸词维度 -0.60】原始问题聚焦于「猫咪表情包梗图」的制作，延伸词「人类幼崽陪伴指南」引入了完全不相关的对象「人类幼崽」和动机「陪伴」，与原始问题的主题和目的完全脱节，属于作用域稀释型，且偏离度极高。\n【最终得分 -0.52】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类用沙想捏出梦里通天塔_r1_q3_3": {
      "type": "sug",
      "query": "[SUG] 人类用沙想捏出梦里通天塔",
      "level": 13,
      "relevance_score": -0.7600000000000001,
      "evaluationReason": "【评估对象】词条\"人类用沙想捏出梦里通天塔\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图，意在表达/反映人类双标行为\n【动机维度 0.00】原始问题的核心动机是「制作」以「反映」某种行为的梗图。sug词条是描述一种人类行为，不包含任何动作意图，因此无法评估动机匹配度。\n【品类维度 -0.80】原始问题主体是「猫咪表情包梗图」、「人类双标行为」；sug词条主体是「人类」、「沙」、「通天塔」。二者在对象层和场景层均无任何交集，品类完全不相关。\n【延伸词维度 -0.60】sug词条「人类用沙想捏出梦里通天塔」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、内容和目的上完全不相关，属于作用域无关型，且严重偏离原始问题，导致稀释作用域。\n【最终得分 -0.76】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类幼仔_r1_q3_4": {
      "type": "sug",
      "query": "[SUG] 人类幼仔",
      "level": 13,
      "relevance_score": -0.7100000000000001,
      "evaluationReason": "【评估对象】词条\"人类幼仔\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，sug词条「人类幼仔」是一个名词短语，没有包含任何动作意图，因此动机维度评分为0。\n【品类维度 -0.85】原始问题核心对象是《猫咪表情包梗图》，限定词有《人类双标行为》。sug词条《人类幼仔》与原始问题主体对象完全不符，且限定词也无关联，品类冲突。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，而延伸词「人类幼仔」引入了与猫咪无关的新对象，稀释了原始问题的核心主题，降低了内容的聚焦度。\n【最终得分 -0.71】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类简史_r1_q3_5": {
      "type": "sug",
      "query": "[SUG] 人类简史",
      "level": 13,
      "relevance_score": -0.6700000000000002,
      "evaluationReason": "【评估对象】词条\"人类简史\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是“制作”表情包梗图。sug词条《人类简史》指代一本书籍，没有明确的动作意图。\n【品类维度 -0.80】原始问题核心对象是“猫咪表情包梗图”和“双标行为”，场景限定为“人类”。sug词条“人类简史”核心对象为“简史”，场景为“人类”，二者对象层和场景层均完全不匹配，品类冲突，属于完全不相关的概念。\n【延伸词维度 -0.15】sug词条「人类简史」与原始问题「制作猫咪表情包梗图」的核心目的和作用域完全不符，属于无关且稀释主题的延伸，降低了内容的针对性。\n【最终得分 -0.67】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类进化史_r1_q3_6": {
      "type": "sug",
      "query": "[SUG] 人类进化史",
      "level": 13,
      "relevance_score": -0.12,
      "evaluationReason": "【评估对象】词条\"人类进化史\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.00】原始问题意在「制作」表情包梗图，而sug词条「人类进化史」为纯名词，无任何动作意图，动机完全不匹配。\n【品类维度 0.00】原始问题核心是“猫咪表情包梗图”及“双标行为主题”。而sug词条“人类进化史”是历史类别，与原始问题在对象层和场景层均无任何关联。\n【延伸词维度 -0.60】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，核心是「制作」和「猫咪表情包梗图」。sug词条「人类进化史」与原始问题在主题、目的和对象上均无关联，属于完全无关的延伸词，严重稀释了原始问题的聚焦度，且引入了完全不相干的信息，对原始目的达成有极强的负面影响。\n【最终得分 -0.12】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类跌落梦境_r1_q3_7": {
      "type": "sug",
      "query": "[SUG] 人类跌落梦境",
      "level": 13,
      "relevance_score": -0.6700000000000002,
      "evaluationReason": "【评估对象】词条\"人类跌落梦境\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「人类跌落梦境」是一个游戏名称，没有体现任何制作的行为意图。\n【品类维度 -0.80】原始问题核心对象是“猫咪表情包梗图”，限定词是“人类双标行为”。sug词条“人类跌落梦境”是一个游戏名，与原始问题的核心对象和限定词均完全不匹配，品类完全冲突。\n【延伸词维度 -0.15】sug词条「人类跌落梦境」是一款游戏名称，与原始问题中「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，属于无关型延伸词，且分散了用户对核心需求的注意力。\n【最终得分 -0.67】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类群星闪耀时_r1_q3_8": {
      "type": "sug",
      "query": "[SUG] 人类群星闪耀时",
      "level": 13,
      "relevance_score": -0.436,
      "evaluationReason": "【评估对象】词条\"人类群星闪耀时\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】sug词条「人类群星闪耀时」是一个作品名称，无法识别出任何动作意图，因此无法与原始问题的核心动作「制作」进行匹配。\n【品类维度 -0.50】原始问题的核心是「猫咪表情包梗图」、「双标行为」。sug词的核心是「人类群星闪耀时」。两者对象层和场景层均无任何关联，品类完全不同，属于品类冲突。\n【延伸词维度 -0.18】sug词条「人类群星闪耀时」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题和目的上完全不相关，属于作用域无关型，且严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.44】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_人类高质量男姓_r1_q3_9": {
      "type": "sug",
      "query": "[SUG] 人类高质量男姓",
      "level": 13,
      "relevance_score": -0.6760000000000002,
      "evaluationReason": "【评估对象】词条\"人类高质量男姓\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」，sug词条「人类高质量男姓」是一个描述性名词短语，没有体现任何动作意图。因此，sug词条无法命中原始问题的动机。\n【品类维度 -0.80】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条「人类高质量男性」与原始问题对象和限定词完全不匹配，品类冲突严重。\n【延伸词维度 -0.18】sug词条「人类高质量男姓」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心主题和目的完全不符，属于无关且稀释原始问题焦点的延伸词，严重偏离了用户意图。\n【最终得分 -0.68】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "q_双标_r1_4": {
      "type": "q",
      "query": "[Q] 双标",
      "level": 12,
      "relevance_score": 0.024,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 2,
      "domain_type": "修饰短语"
    },
    "sug_双标是什么意思_r1_q4_0": {
      "type": "sug",
      "query": "[SUG] 双标是什么意思",
      "level": 13,
      "relevance_score": 0.0050000000000000044,
      "evaluationReason": "【评估对象】词条\"双标是什么意思\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】「制作」猫咪表情包梗图，用于「反映」人类双标行为。核心动作是「制作」和「反映」\n【动机维度 0.00】原始问题的核心动机是「制作」和「反映」。sug词条「双标是什么意思」的核心动机是「了解/理解」。sug词条仅包含原始问题的主题「双标」，但没有围绕原始问题的核心动作「制作」或「反映」提供任何动机支持，因此动机不匹配。\n【品类维度 0.05】原始问题核心是《猫咪表情包梗图制作》，限定词是《人类双标行为》。sug词条仅包含《双标》，与原始问题的核心对象层《猫咪表情包梗图》几乎无关，覆盖度极低。\n【延伸词维度 -0.15】sug词条「双标是什么意思」中的「是什么意思」是延伸词，它将原始问题从「制作」行为转移到「解释」概念，稀释了原始问题制作梗图的聚焦度，降低了内容针对性。\n【最终得分 0.01】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_讽刺双标的文案_r1_q4_1": {
      "type": "sug",
      "query": "[SUG] 讽刺双标的文案",
      "level": 13,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"讽刺双标的文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成（梗图）\n【动机维度 -0.15】原始问题的核心动机是「制作（梗图）」，sug词条的动机是「撰写/找寻（文案）」。两者动机存在部分重合，但方向上制作（图像）与撰写（文字）存在明显偏差。\n【品类维度 0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「文案」，场景层为「讽刺双标」。场景层有部分匹配，但核心对象层「猫咪表情包梗图」与「文案」完全不符。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，延伸词「文案」虽然与「讽刺双标」相关，但偏离了「制作」和「猫咪表情包」的核心对象，引入了不相关的创作形式，稀释了原始问题的聚焦度。\n【最终得分 0.01】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_双标的人是什么心理_r1_q4_2": {
      "type": "sug",
      "query": "[SUG] 双标的人是什么心理",
      "level": 13,
      "relevance_score": -0.07999999999999999,
      "evaluationReason": "【评估对象】词条\"双标的人是什么心理\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），通过猫咪表情包梗图反映人类双标行为，旨在表达或讽刺\n【动机维度 0.00】原始问题的核心动机是「制作」反映特定主题的表情包梗图，带有「表达、讽刺」的意图。sug词条「双标的人是什么心理」不含显性动机，也无法推断出隐性动机。sug词条不包含任何动作意图，因此无法与原始问题的动机「制作」进行匹配。\n【品类维度 0.05】原始问题核心对象是《猫咪表情包梗图》，场景是《人类双标行为》。sug词条仅包含《双标》，且仅为泛化概念，与问题核心对象完全不对应，品类差异大。\n【延伸词维度 -0.60】sug词条「双标的人是什么心理」与原始问题「制作猫咪表情包梗图」的核心目的完全不符。原始问题是关于内容创作，而sug词条是心理学探讨，引入了完全不相关的概念，严重稀释了原始问题的聚焦度，导致负向评分。\n【最终得分 -0.08】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_双标文案_r1_q4_3": {
      "type": "sug",
      "query": "[SUG] 双标文案",
      "level": 13,
      "relevance_score": -0.23,
      "evaluationReason": "【评估对象】词条\"双标文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「双标文案」未体现任何明确的动作意图。因此，sug词条无法匹配原始问题的动机。\n【品类维度 -0.25】原始问题是关于《猫咪表情包梗图》且反映《人类双标行为》，而sug词条是《双标文案》。sug词条无法命中核心对象，且限定词不同，属于品类错位。\n【延伸词维度 -0.15】原始问题聚焦于制作「猫咪表情包梗图」以反映「人类双标行为」，而sug词条「双标文案」将重点从「表情包梗图」转移到「文案」，且未提及「猫咪」元素，稀释了原始问题的核心对象和产出形式，属于作用域稀释型。\n【最终得分 -0.23】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_双标高爆卡点伴奏_r1_q4_4": {
      "type": "sug",
      "query": "[SUG] 双标高爆卡点伴奏",
      "level": 13,
      "relevance_score": -0.7100000000000001,
      "evaluationReason": "【评估对象】词条\"双标高爆卡点伴奏\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包/梗图，而sug词条「双标高爆卡点伴奏」没有体现任何动作意图，因此动机不匹配。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，涉及「人类双标行为」限定词；sug词条对象层为「卡点伴奏」，主核心词与限定词均不匹配，品类完全冲突，负相关。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调内容创作和主题。sug词条「双标高爆卡点伴奏」中的「高爆卡点伴奏」与原始问题的「制作表情包梗图」这一核心目的和对象完全不符，引入了音乐制作和视频剪辑的无关维度，严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.71】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_双标信用卡_r1_q4_5": {
      "type": "sug",
      "query": "[SUG] 双标信用卡",
      "level": 13,
      "relevance_score": -0.7600000000000001,
      "evaluationReason": "【评估对象】词条\"双标信用卡\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题核心动机是「制作」图片作品，而sug词条「双标信用卡」无任何制作行为，sug词条无法识别动作意图，动机完全不匹配。\n【品类维度 -0.80】原始问题核心是「猫咪表情包梗图」，限定词为「反映人类双标行为」。Sug词「双标信用卡」的核心对象是「信用卡」，且限定词「双标」与原始问题中的「双标行为」含义完全不同，品类错位严重。\n【延伸词维度 -0.60】原始问题聚焦于「猫咪表情包梗图」的制作，延伸词「信用卡」与原始问题的核心主题完全无关，属于作用域无关型，且严重偏离原始问题，导致稀释作用域，故给予负分。\n【最终得分 -0.76】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_双椒兔做法_r1_q4_6": {
      "type": "sug",
      "query": "[SUG] 双椒兔做法",
      "level": 13,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"双椒兔做法\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】sug词条「双椒兔做法」的动机是“如何制作/烹饪”，原始问题是“如何制作”，虽然都有制作，但是二者制作的客体完全不同，且sug词条中的‘做法’已经特指「食品」的制作方法，无法与原始问题意图相匹配。\n【品类维度 -0.80】原始问题的核心主体是“猫咪表情包梗图”和“双标行为”，sug词为“双椒兔做法”，对象完全不匹配，一个为食品制作，一个为文化创作，品类差异巨大。\n【延伸词维度 -0.60】sug词条「双椒兔做法」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」在主题、对象、目的上完全不相关，引入了与原始问题核心需求无关的全新概念，严重稀释了原始问题的聚焦度，导致内容完全偏离。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_双标图片_r1_q4_7": {
      "type": "sug",
      "query": "[SUG] 双标图片",
      "level": 13,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"双标图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，sug词条“双标图片”不包含任何动作意图，因此无法匹配。\n【品类维度 0.25】原始问题中包含核心对象“猫咪表情包梗图”和限定词“双标行为”。sug词条只包含了限定词“双标行为”的对象部分，缺失了核心对象“猫咪表情包梗图”，覆盖度较低。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」这一特定形式，而sug词条「图片」泛化了对象，稀释了原始问题的具体性和趣味性，属于作用域稀释型。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_双标表情包_r1_q4_8": {
      "type": "sug",
      "query": "[SUG] 双标表情包",
      "level": 13,
      "relevance_score": 0.4,
      "evaluationReason": "【评估对象】词条\"双标表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】sug词条「双标表情包」不包含明确的动作意图。原始问题的核心动机是「制作」，而sug词条仅提及了表情包的主题，未能体现出任何制作或获取表情包的动作。\n【品类维度 0.50】原始问题涉及“猫咪表情包梗图”和“双标行为”两个核心对象。sug词条“双标表情包”包含了“双标”和“表情包”，覆盖了原始问题大部分核心对象层，但缺失了“猫咪”这一关键限定词\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。\n【最终得分 0.40】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_双标的人_r1_q4_9": {
      "type": "sug",
      "query": "[SUG] 双标的人",
      "level": 13,
      "relevance_score": 0.04000000000000001,
      "evaluationReason": "【评估对象】词条\"双标的人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，sug词条「双标的人」只是一个名词短语，它本身不包含任何动作意图，也无法体现与“制作”相关的行为。\n【品类维度 0.05】原始问题核心对象是《猫咪表情包梗图》，限定词是《人类双标行为》。sug词《双标的人》虽然提及《双标》，但主体是《人》，与原始问题的核心对象《猫咪表情包梗图》完全不匹配，同时，sug词条只涉及原始问题的一小部分语义信息《双标》，导致匹配度较低。覆盖度极低。\n【延伸词维度 0.00】sug词条「双标的人」是原始问题「人类双标行为」的同义表达，属于原始问题作用域内的词汇，不构成延伸词。\n【最终得分 0.04】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "q_行为_r1_5": {
      "type": "q",
      "query": "[Q] 行为",
      "level": 12,
      "relevance_score": 0.024,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 2,
      "domain_type": "修饰短语"
    },
    "sug_行为心理学_r1_q5_0": {
      "type": "sug",
      "query": "[SUG] 行为心理学",
      "level": 13,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"行为心理学\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是\"制作\"，而sug词条「行为心理学」无明确的动作意图。因此，动机维度不匹配。\n【品类维度 0.05】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条「行为心理学」是高度泛化的学科概念，其内容与「双标行为」有抽象关联，但与图片制作无直接主体关联，覆盖度极低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，而「行为心理学」是一个宽泛的学术领域，与具体的制作行为关联度低，稀释了原始问题的目的性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为基础_r1_q5_1": {
      "type": "sug",
      "query": "[SUG] 行为基础",
      "level": 13,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"行为基础\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条“行为基础”是一个名词短语，不包含任何动作意图，因此动机意图完全不匹配。\n【品类维度 0.05】原始问题是关于《人类双标行为》、《猫咪表情包梗图》的具体制作方法。sug词条《行为基础》过于抽象和泛化，无法构成有效内容主体匹配。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，且主题是「人类双标行为」。sug词条「行为基础」是一个非常宽泛且抽象的词汇，与原始问题的具体制作行为和特定主题关联度极低，属于作用域稀释型延伸词，分散了原始问题的核心焦点。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为规范手抄报_r1_q5_2": {
      "type": "sug",
      "query": "[SUG] 行为规范手抄报",
      "level": 13,
      "relevance_score": -0.3350000000000001,
      "evaluationReason": "【评估对象】词条\"行为规范手抄报\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），通过制作表达观点\n【动机维度 0.00】原始问题的核心动机是「制作」具有特定表达意图的梗图。sug词条「行为规范手抄报」的动机是「制作」手抄报，虽然都包含「制作」的动作，但是意图载体和目的完全不匹配。\n【品类维度 -0.80】原始问题内容主体为《人类双标行为的猫咪表情包梗图》，作用域为『猫咪、表情包梗图、人类双标行为』；sug词条内容主体为《行为规范手抄报》，作用域为『行为规范、手抄报』。二者核心对象和限定词完全不同，品类高度不匹配。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，而sug词条「行为规范手抄报」引入了完全不相关的「手抄报」和「行为规范」概念，严重稀释了原始问题的核心主题和目的，属于作用域稀释型。\n【最终得分 -0.34】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为习惯手抄报_r1_q5_3": {
      "type": "sug",
      "query": "[SUG] 行为习惯手抄报",
      "level": 13,
      "relevance_score": -0.7100000000000001,
      "evaluationReason": "【评估对象】词条\"行为习惯手抄报\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条是「行为习惯手抄报」，未包含任何明确的动作意图。因此，sug词条与原始问题的动机无匹配。\n【品类维度 -0.85】原始问题的核心对象是“表情包梗图”，限定词为“猫咪”、“双标行为”，sug词条为“行为习惯手抄报”。两者对象类型完全不匹配，无任何共同限定词，品类冲突严重。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，强调「人类双标行为」这一主题。sug词条「行为习惯手抄报」中的「手抄报」与原始问题中的「表情包梗图」在形式上完全不符，且「行为习惯」也未能体现「人类双标行为」这一核心主题，属于引入无关信息，稀释了原始问题的聚焦度。\n【最终得分 -0.71】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为艺术_r1_q5_4": {
      "type": "sug",
      "query": "[SUG] 行为艺术",
      "level": 13,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"行为艺术\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图，用于反映人类双标行为\n【动机维度 0.00】原始问题的核心动机是「制作」梗图，sug词条「行为艺术」没有包含任何动作意图，因此无法评估动作匹配度。\n【品类维度 -0.20】原始问题侧重“猫咪表情包梗图”这一内容形式与“双标行为”这一具体主题，sug词条“行为艺术”虽与“行为”相关，但内容主体差异大，无法直接匹配，存在一定偏离。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，而「行为艺术」是一个宽泛的艺术形式，与制作表情包梗图的直接关联性较低，稀释了原始问题的具体制作目的。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为决定关系而非关系决定行为_r1_q5_5": {
      "type": "sug",
      "query": "[SUG] 行为决定关系而非关系决定行为",
      "level": 13,
      "relevance_score": -0.07,
      "evaluationReason": "【评估对象】词条\"行为决定关系而非关系决定行为\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是“制作”表情包梗图，sug词条「行为决定关系而非关系决定行为」无任何动作意图，无法评估动机匹配度。\n【品类维度 -0.05】原始问题核心对象是「猫咪表情包梗图」、「人类双标行为」，强调制作。sug词条是抽象的观点陈述，与原始问题无任何核心对象和场景匹配，存在语义错位，可能会引起用户迷惑，用户误解为制作表情包梗图而搜索。\n【延伸词维度 -0.15】sug词条「行为决定关系而非关系决定行为」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，属于无关型延伸词，且分散了用户对制作表情包的注意力，稀释了原始问题的聚焦度。\n【最终得分 -0.07】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为违反腾讯用户协议_r1_q5_6": {
      "type": "sug",
      "query": "[SUG] 行为违反腾讯用户协议",
      "level": 13,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"行为违反腾讯用户协议\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题的核心动机是「制作」表情包，而Sug词条「行为违反腾讯用户协议」并没有提出任何动作意图，因此无法匹配。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条与原始问题在对象层和场景层均完全不匹配，是完全不相关的安全提示。\n【延伸词维度 -0.60】原始问题聚焦于「制作猫咪表情包梗图」这一创意行为，而sug词条「行为违反腾讯用户协议」引入了与创作内容和方法完全无关的法律/平台规范维度，严重稀释了原始问题的核心目的和作用域，属于作用域稀释型延伸词。\n【最终得分 -0.80】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为认知疗法_r1_q5_7": {
      "type": "sug",
      "query": "[SUG] 行为认知疗法",
      "level": 13,
      "relevance_score": -0.6700000000000002,
      "evaluationReason": "【评估对象】词条\"行为认知疗法\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），通过制作来反映人类双标行为，表达创作意图\n【动机维度 0.00】原始问题的核心动机是「制作」带有特定主题的表情包梗图，而sug词条「行为认知疗法」中没有明确的动作语义，因此无法评估动作匹配度。\n【品类维度 -0.80】原始问题核心是“猫咪表情包梗图”，限定词是“人类双标行为”；sug词是“行为认知疗法”，对象和目的完全不同，品类错位严重。\n【延伸词维度 -0.15】原始问题聚焦于「制作表情包梗图」，而「行为认知疗法」是一个心理学概念，与表情包制作完全无关，属于无关型延伸词，且引入了完全不相关的专业领域，稀释了原始问题的聚焦度。\n【最终得分 -0.67】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为经济学_r1_q5_8": {
      "type": "sug",
      "query": "[SUG] 行为经济学",
      "level": 13,
      "relevance_score": -0.43000000000000005,
      "evaluationReason": "【评估对象】词条\"行为经济学\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】sug词条「行为经济学」没有明确的动作意图，因此无法评估其与原始问题「制作」这一动作意图的匹配度。\n【品类维度 -0.50】原始问题核心是「人类双标行为」和「猫咪表情包梗图」。sug词是「行为经济学」，两者品类完全不匹配，核心对象和限定词均无关联。\n【延伸词维度 -0.15】sug词条「行为经济学」与原始问题「制作猫咪表情包梗图」的核心目的和作用域完全不符，属于无关且稀释主题的延伸，降低了内容的针对性。\n【最终得分 -0.43】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_行为规范家_r1_q5_9": {
      "type": "sug",
      "query": "[SUG] 行为规范家",
      "level": 13,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"行为规范家\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】「制作」猫咪表情包梗图，用于「反映」人类双标行为\n【动机维度 0.00】原始问题明确意图为「制作」梗图，sug词条「行为规范家」无明确动作意图，且与「制作」、「反映」的核心动作完全不匹配。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，限定词为“双标行为”。sug词为“行为规范家”，对象完全不符，且限定词无关联，无法体现人类双标行为，品类冲突。\n【延伸词维度 -0.15】原始问题是关于制作特定主题的表情包梗图，而“行为规范家”是一个抽象的概念，与表情包制作这一具体行为和猫咪、双标等主题均不相关。它引入了与原始问题核心目的无关的全新概念，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "q_猫咪_r1_6": {
      "type": "q",
      "query": "[Q] 猫咪",
      "level": 12,
      "relevance_score": 0.09,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 3,
      "domain_type": "中心名词"
    },
    "sug_猫咪领养免费领养_r1_q6_0": {
      "type": "sug",
      "query": "[SUG] 猫咪领养免费领养",
      "level": 13,
      "relevance_score": -0.27,
      "evaluationReason": "【评估对象】词条\"猫咪领养免费领养\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 0.00】原始问题的核心动机是「制作」梗图，而sug词条「猫咪领养免费领养」的动机是「领养」，两者动作意图完全无关。sug词条中包含猫咪，但主题无关。\n【品类维度 -0.55】原始问题涉及“猫咪+表情包梗图”，sug词为“猫咪领养”，两者对象层和场景层均完全不匹配，品类冲突。\n【延伸词维度 -0.50】原始问题聚焦于「制作表情包梗图」这一创意行为，对象是「猫咪」和「人类双标行为」。sug词条「猫咪领养免费领养」引入了「领养」这一全新且与原始问题核心目的完全无关的维度，严重稀释了原始问题的聚焦度，甚至将主题完全转向了另一个方向，因此给予负向评分。\n【最终得分 -0.27】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪叫声吸引小猫_r1_q6_1": {
      "type": "sug",
      "query": "[SUG] 猫咪叫声吸引小猫",
      "level": 13,
      "relevance_score": -0.26,
      "evaluationReason": "【评估对象】词条\"猫咪叫声吸引小猫\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是“制作”表情包梗图，sug词条“猫咪叫声吸引小猫”的意图是“吸引”（小猫），两者动作意图完全不相关。\n【品类维度 -0.50】原始问题核心对象为「表情包梗图」及「人类双标行为」，限定词为「猫咪」。sug词条核心对象为「猫咪叫声」及「小猫」，两者在核心对象和限定词上均不匹配，品类完全冲突。\n【延伸词维度 -0.60】sug词条中的“叫声”、“吸引”、“小猫”均与原始问题“制作反映人类双标行为的猫咪表情包梗图”的核心目的和作用域完全不符，引入了完全不相关的概念，严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.26】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪呕吐_r1_q6_2": {
      "type": "sug",
      "query": "[SUG] 猫咪呕吐",
      "level": 13,
      "relevance_score": -0.436,
      "evaluationReason": "【评估对象】词条\"猫咪呕吐\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题的核心动机是「制作」表情包，而sug词条「猫咪呕吐」没有明确的动作意图。因此，sug词条无法命中原始问题的动机。\n【品类维度 -0.50】原始问题核心对象为「猫咪表情包梗图」，限定词「反映人类双标行为」。Sug词条核心对象为「猫咪呕吐」，二者对象主体和限定词均不匹配，品类完全冲突。\n【延伸词维度 -0.18】sug词条「猫咪呕吐」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关信息，严重稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.44】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪头像_r1_q6_3": {
      "type": "sug",
      "query": "[SUG] 猫咪头像",
      "level": 13,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"猫咪头像\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「猫咪头像」是纯名词，不包含任何动作意图，因此动机匹配度为0。\n【品类维度 -0.20】原始问题是关于『猫咪表情包梗图』，sug词条是『猫咪头像』。对象层「猫咪」匹配，但原始问题有更具体的「表情包梗图」这一核心对象，而sug词条是「头像」，存在品类错位，无法满足核心需求。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，强调制作、双标行为、表情包和梗图。sug词条「猫咪头像」与原始问题的核心目的「制作表情包梗图」关联度低，且「头像」与「表情包梗图」并非同义或细化关系，属于无关型延伸词。它稀释了原始问题中「制作」和「双标行为」的聚焦度，降低了内容的针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪取名_r1_q6_4": {
      "type": "sug",
      "query": "[SUG] 猫咪取名",
      "level": 13,
      "relevance_score": -0.23500000000000004,
      "evaluationReason": "【评估对象】词条\"猫咪取名\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题意图是「制作表情包」，而sug词条「猫咪取名」意图是「取名」。两者动作意图完全不匹配，且sug词条无明确动机层。因此，动机维度得分为0。\n【品类维度 -0.55】原始问题核心对象是《猫咪表情包梗图》，作用域包含《人类双标行为》。Sug词条核心对象为《猫咪取名》，两者对象完全错位，品类冲突严重，因此得分低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，核心是「制作」和「表情包梗图」。「猫咪取名」与原始问题的核心目的和作用域完全不相关，引入了无关信息，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.24】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪品种_r1_q6_5": {
      "type": "sug",
      "query": "[SUG] 猫咪品种",
      "level": 13,
      "relevance_score": -0.43000000000000005,
      "evaluationReason": "【评估对象】词条\"猫咪品种\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题意图是「制作」表情包，sug词条「猫咪品种」无任何动作意图，因此无法评估动作匹配度。\n【品类维度 -0.50】原始问题核心对象为「猫咪表情包梗图」及「双标行为」，限定词为「人类」。sug词条「猫咪品种」虽含「猫咪」，但将对象层从「表情包梗图」变为「品种」，完全不匹配，且缺失所有限定词。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「双标行为」的「猫咪表情包梗图」，核心是创意和制作过程。「猫咪品种」与制作表情包梗图的核心目的和作用域无关，属于无关信息，稀释了原始问题的聚焦度。\n【最终得分 -0.43】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪搞笑视频_r1_q6_6": {
      "type": "sug",
      "query": "[SUG] 猫咪搞笑视频",
      "level": 13,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"猫咪搞笑视频\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图，核心动作是「制作」。sug词条「猫咪搞笑视频」没有包含制作的动作意图。因此，该词条与原始问题的动机不匹配。\n【品类维度 0.05】sug词条《猫咪搞笑视频》与原始问题《如何制作反映人类双标行为的猫咪表情包梗图》完全不同。原始问题是关于特定主题的表情包梗图，而sug词条是通用的搞笑视频，缺乏匹配的限定词和具体对象层。但有主体词《猫咪》，主题和形式都不一致。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」。sug词条「猫咪搞笑视频」中的「搞笑视频」是延伸词，它将原始问题的「表情包梗图」这一对象层替换为「视频」，且「搞笑」这一动机层也与原始问题的「反映双标行为」这一深层动机不符，稀释了原始问题的核心目的和对象。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪叫声_r1_q6_7": {
      "type": "sug",
      "query": "[SUG] 猫咪叫声",
      "level": 13,
      "relevance_score": -0.43000000000000005,
      "evaluationReason": "【评估对象】词条\"猫咪叫声\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”。sug词条“猫咪叫声”缺乏明确的动机意图，无法与原始问题的“制作”动作匹配。\n【品类维度 -0.50】原始问题核心是「猫咪表情包梗图」，场景为「反映人类双标行为」。sug词条「猫咪叫声」是完全不同的品类，与原始问题的核心对象和场景均不匹配，存在品类冲突。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，核心是创意和制作。sug词条「猫咪叫声」与原始问题的核心目的和作用域完全不符，属于无关信息，稀释了原始问题的聚焦度。\n【最终得分 -0.43】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪驱虫药推荐_r1_q6_8": {
      "type": "sug",
      "query": "[SUG] 猫咪驱虫药推荐",
      "level": 13,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"猫咪驱虫药推荐\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是\"制作\"表情包梗图。sug词条\"猫咪驱虫药推荐\"的动机是\"获取推荐\"信息，与原始问题的\"制作\"动机完全不相关。\n【品类维度 -0.80】原始问题核心对象为「猫咪表情包梗图」及限定词「人类双标行为」，sug词条核心对象为「驱虫药」，限定词为「猫咪」，两者主体物品完全不一致，品类冲突严重。\n【延伸词维度 -0.60】原始问题聚焦于「制作表情包梗图」这一创意行为，对象是「猫咪」和「人类双标行为」。sug词条「猫咪驱虫药推荐」引入了与原始问题完全无关的「驱虫药」和「推荐」概念，属于作用域无关型延伸词，且与原始问题核心目的完全不符，严重稀释了原始问题的聚焦度，导致负向评分。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "sug_猫咪黑下巴怎么处理_r1_q6_9": {
      "type": "sug",
      "query": "[SUG] 猫咪黑下巴怎么处理",
      "level": 13,
      "relevance_score": -0.218,
      "evaluationReason": "【评估对象】词条\"猫咪黑下巴怎么处理\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，sug词条意图是「处理」猫咪黑下巴问题。两者动作意图完全不匹配，且一个侧重内容创作，一个侧重问题解决方案。\n【品类维度 -0.50】原始问题对象层为「人类双标行为的猫咪表情包梗图」，场景层无。sug词条对象层为「猫咪黑下巴」，场景层无。两者对象层完全不同，品类错位。\n【延伸词维度 -0.18】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，核心是创意和制作。sug词条「猫咪黑下巴怎么处理」引入了「猫咪健康护理」这一完全不相关的领域，与原始问题的「制作」和「双标行为」主题没有任何关联，严重稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.22】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.09
    },
    "q_表情包_r1_7": {
      "type": "q",
      "query": "[Q] 表情包",
      "level": 12,
      "relevance_score": 0.15,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 3,
      "domain_type": "中心名词"
    },
    "sug_表情包抽象_r1_q7_0": {
      "type": "sug",
      "query": "[SUG] 表情包抽象",
      "level": 13,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"表情包抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 0.00】原始问题的核心动机是「制作」反映特定主题的梗图。sug词条「表情包抽象」仅为名词短语，无明确的动作意图，无法评估动作匹配度。\n【品类维度 0.08】原始问题意图明确且限定词清晰，对象层是『梗图』，限定词包括『人类双标行为』和『猫咪表情包』；sug词是『表情包抽象』，仅包含『表情包』这一个核心名词，且是抽象概念，与原问题具体概念差距大，覆盖度较低。\n【延伸词维度 -0.15】sug词条「抽象」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和对象均不匹配，稀释了原始问题的具体性和聚焦度，属于作用域稀释型。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "sug_表情包怎么制作_r1_q7_1": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作",
      "level": 13,
      "relevance_score": 0.695,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.98】原始问题核心动机是“制作”，sug词条「表情包怎么制作」的核心动机也是“制作”，两者核心动作完全一致，具备高度匹配性。\n【品类维度 0.55】原始问题对象层包含「表情包」「梗图」「猫咪」，场景层包含「双标行为」；sug词条仅包含对象层「表情包」。匹配度一般，因为sug词条只部分提及了核心对象，而大量相关限定词缺失。\n【延伸词维度 -0.15】sug词条「表情包怎么制作」仅提及制作方法，而原始问题明确了制作对象「猫咪表情包梗图」、主题「反映人类双标行为」，sug词条的延伸词「怎么制作」过于宽泛，稀释了原始问题的具体性和聚焦度，属于作用域稀释型。\n【最终得分 0.69】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.15
    },
    "sug_表情包可爱_r1_q7_2": {
      "type": "sug",
      "query": "[SUG] 表情包可爱",
      "level": 13,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"表情包可爱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」，sug词条「表情包可爱」没有体现任何动作意图，因此无法评估动作匹配度。\n【品类维度 0.05】原始问题涉及“猫咪表情包梗图”，sug词为“表情包”，对象层有部分匹配，但sug词过度泛化且缺失了“猫咪”、“梗图”以及“双标行为”等所有限定词。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调内容和形式的特定性。「可爱」作为延伸词，与原始问题中的「双标行为」和「梗图」的核心目的不符，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "sug_表情包图片大全_r1_q7_3": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全",
      "level": 13,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"表情包图片大全\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），通过描绘猫咪来反映人类双标行为。\n【动机维度 0.00】原始问题的核心动机是\"制作\"某种具有特定主题和目的的表情包梗图。Sug词条\"表情包图片大全\"是纯名词短语，无任何动作意图，因此无法与原始问题的\"制作\"动作进行匹配，动机维度得分为0。\n【品类维度 0.25】sug词条仅包含核心对象“表情包图片”，但缺失了原始问题中所有的限定词和更具体的对象描述（人类双标行为、猫咪、梗图），覆盖度低，但品类仍相关。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调「人类双标行为」这一核心概念。sug词条「图片大全」与原始问题的「制作」和「特定主题」无直接关联，稀释了原始问题的核心目的和聚焦度，属于作用域稀释型。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.15
    },
    "sug_表情包搞笑配文_r1_q7_4": {
      "type": "sug",
      "query": "[SUG] 表情包搞笑配文",
      "level": 13,
      "relevance_score": -0.19,
      "evaluationReason": "【评估对象】词条\"表情包搞笑配文\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.15】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「表情包搞笑配文」的隐含动机是「使用/寻找」搞笑配文，与原始问题的「制作」存在一定偏离，但两者都是围绕表情包展开动作。\n【品类维度 -0.25】原始问题涉及“猫咪表情包梗图”和“人类双标行为”的特定主题。sug词条「表情包搞笑配文」虽有“表情包”这一共同对象，但限定过于泛化，未体现「猫咪」和「双标行为」的核心场景与性质，且「配文」未完全匹配「梗图」的图文结合形式。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调了制作方法、主题和对象。sug词条「搞笑配文」虽然与表情包相关，但它将主题从「人类双标行为」泛化为「搞笑」，且将「制作」行为缩小为「配文」，稀释了原始问题的核心主题和制作的复杂性，属于作用域稀释型。\n【最终得分 -0.19】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "sug_表情包发给女朋友_r1_q7_5": {
      "type": "sug",
      "query": "[SUG] 表情包发给女朋友",
      "level": 13,
      "relevance_score": -0.12000000000000001,
      "evaluationReason": "【评估对象】词条\"表情包发给女朋友\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 -0.05】原始问题是“制作”表情包梗图，而sug词条是“发给”表情包，两者都包含表情包，但原始问题为主动的制作行为，sug词条是分享行为，两者动作意图走向不同但有微弱关联。\n【品类维度 -0.20】原始问题需求的是制作「反映人类双标行为的猫咪表情包梗图」，而sug词条「表情包发给女朋友」限定了接收对象，失去了主体和客体以及限定词。\n【延伸词维度 -0.15】sug词条「表情包发给女朋友」中的“发给女朋友”是延伸词，它引入了原始问题未提及的社交场景和接收对象，稀释了原始问题关于“制作”和“内容”的核心聚焦，降低了内容的针对性。\n【最终得分 -0.12】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "sug_表情包简笔画_r1_q7_6": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画",
      "level": 13,
      "relevance_score": 0.18,
      "evaluationReason": "【评估对象】词条\"表情包简笔画\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.35】原始问题核心动机是「制作」反映双标行为的猫咪表情包梗图。sug词条「表情包简笔画」包含「表情包」这一对象和「简笔画」这一制作方式，与原始问题的「制作」动机有一定关联但语义不完全一致，因此为弱相关。\n【品类维度 0.05】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。Sug词条对象层为「表情包简笔画」。核心对象「表情包」匹配，但sug词条内容主体缺失「猫咪个体」及所有限定词，且泛化为「简笔画」\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的特定主题创作，而sug词条「简笔画」引入了与原始问题主题和目的关联度较低的绘画风格，稀释了原始问题的核心创作意图，降低了内容的针对性。\n【最终得分 0.18】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.15
    },
    "sug_表情包模板_r1_q7_7": {
      "type": "sug",
      "query": "[SUG] 表情包模板",
      "level": 13,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"表情包模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题是关于『制作』表情包梗图，而sug词条「表情包模板」没有明确的动作意图。因此，sug词条在动机维度上无法匹配。\n【品类维度 0.08】原始问题是关于“制作人类双标行为的猫咪表情包梗图”，sug词条仅有“表情包模板”，是宽泛概念，无法具体匹配原始问题的核心主体“猫咪表情包梗图”和限定词“人类双标行为”。仅在最泛化的对象层面上匹配，故得分较低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体创意和内容，而sug词条「表情包模板」仅提供了制作工具的通用素材，与原始问题的核心创意和内容关联度低，稀释了原始问题的聚焦度。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "sug_表情包发给男朋友_r1_q7_8": {
      "type": "sug",
      "query": "[SUG] 表情包发给男朋友",
      "level": 13,
      "relevance_score": -0.14500000000000002,
      "evaluationReason": "【评估对象】词条\"表情包发给男朋友\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 -0.10】原始问题动机是“制作”梗图，而sug词条的动机是“发送/分享”表情包。两者虽然都与表情包相关，但动作意图存在方向性差异，制作是生成行为，发送是传播行为。\n【品类维度 -0.20】原始问题求“猫咪表情包梗图”，sug词条为“表情包”。sug词条对象层有“表情包”匹配，但限定词“猫咪”、“梗图”、“双标行为”缺失；sug词条加入新的限定词“男朋友”形成语义错位，故评分偏低。\n【延伸词维度 -0.15】延伸词“发给男朋友”引入了新的场景和对象，与原始问题“制作”表情包的核心目的和内容（人类双标行为的猫咪表情包梗图）无关，稀释了原始问题的聚焦度。\n【最终得分 -0.15】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "sug_表情包制作赚钱_r1_q7_9": {
      "type": "sug",
      "query": "[SUG] 表情包制作赚钱",
      "level": 13,
      "relevance_score": -0.16500000000000004,
      "evaluationReason": "【评估对象】词条\"表情包制作赚钱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 -0.10】原始问题意图是「制作」表情包，sug词条意图是「制作」并「赚钱」。虽然都包含「制作」，但sug多了「赚钱」这个目的，导致动机方向略有偏离。\n【品类维度 -0.25】原始问题对象层为「表情包梗图」，场景层为「人类双标行为」和「猫咪」。Sug词仅对象层有「表情包」，但新增了意图「赚钱」，且限定词均不匹配，存在误导性。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定内容和主题，而sug词条「赚钱」引入了商业变现的维度。这与原始问题的创作目的和内容方向无关，稀释了原始问题的聚焦度，使其偏离了核心的创作意图。\n【最终得分 -0.17】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.15
    },
    "q_梗图_r1_8": {
      "type": "q",
      "query": "[Q] 梗图",
      "level": 12,
      "relevance_score": 0.024,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "domain_index": 3,
      "domain_type": "中心名词"
    },
    "sug_梗图素材_r1_q8_0": {
      "type": "sug",
      "query": "[SUG] 梗图素材",
      "level": 13,
      "relevance_score": 0.21000000000000002,
      "evaluationReason": "【评估对象】词条\"梗图素材\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图。Sug词条「梗图素材」指向的是「获取素材」的动机，其本身无明确动词，无法与制作的动作匹配。\n【品类维度 0.50】sug词条《梗图素材》与原始问题中的核心对象词《梗图》匹配。原始问题中的《表情包》可以被《梗图》包含，作为一种具体的《梗图》类型。缺失了《猫咪》、《双标行为》等所有的限定词，但核心对象仍匹配。\n【延伸词维度 0.10】原始问题是制作梗图，sug词条「素材」是制作梗图的必要组成部分，属于作用域辅助型延伸词，对核心目的有辅助作用。\n【最终得分 0.21】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_梗图搞笑_r1_q8_1": {
      "type": "sug",
      "query": "[SUG] 梗图搞笑",
      "level": 13,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图搞笑\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是“制作”梗图，而sug词条“梗图搞笑”无法识别明确的动作意图。sug词条缺失动机层，因此动机维度评分为0。\n【品类维度 0.08】原始问题核心对象为「猫咪表情包梗图」，场景为「反映人类双标行为」。sug词条「梗图搞笑」只泛化匹配到“梗图”，且缺失所有限定词，匹配度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调制作方法和内容主题。「搞笑」是梗图的普遍属性，但并非原始问题核心，且「梗图搞笑」未能体现原始问题中的「制作」和「人类双标行为」等关键信息，稀释了原始问题的聚焦度。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_梗图精神状态_r1_q8_2": {
      "type": "sug",
      "query": "[SUG] 梗图精神状态",
      "level": 13,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图精神状态\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”梗图，而sug词条“梗图精神状态”中没有明确的动作意图（即无法识别是制作、查找还是欣赏等）。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词较多。Sug词条「梗图精神状态」对象为「梗图」但限定词「精神状态」与原始问题语义不符且无法推断出「猫咪」限定，品类冲突。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调创作过程和具体内容。「精神状态」作为延伸词，与原始问题的核心「制作」和「猫咪表情包」无直接关联，且稀释了原始问题中「人类双标行为」这一具体主题的聚焦度，属于作用域稀释型。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_梗图meme_r1_q8_3": {
      "type": "sug",
      "query": "[SUG] 梗图meme",
      "level": 13,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"梗图meme\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.00】原始问题意图是「制作」反映特定主题的「猫咪表情包梗图」，而sug词条「梗图meme」只提及了对象「梗图」，没有包含任何动作意图，因此动机匹配度为0。\n【品类维度 0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条仅包含通用对象层「梗图」，缺失核心限定词「猫咪表情包」和所有场景层信息，覆盖度较低。\n【延伸词维度 -0.15】sug词条「梗图meme」中的「meme」是「梗图」的同义词，不构成延伸。但sug词条仅包含「梗图」，未能体现原始问题中「制作」、「人类双标行为」、「猫咪表情包」等核心要素，导致信息缺失，稀释了原始问题的聚焦度。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_梗图双人_r1_q8_4": {
      "type": "sug",
      "query": "[SUG] 梗图双人",
      "level": 13,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图双人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是学习「制作」表情包梗图。平台sug词条「梗图双人」描述了梗图这一对象类型，但没有包含任何动机动作，因此动机维度评分为0。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。Sug词条虽然有「梗图」，但主体从「猫咪」变为「双人」，核心对象错位，且丢失限定词。\n【延伸词维度 -0.15】sug词条「双人」与原始问题「猫咪表情包梗图」的核心对象和制作目的无关，引入了不必要的限定，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_梗图抽象_r1_q8_5": {
      "type": "sug",
      "query": "[SUG] 梗图抽象",
      "level": 13,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是“制作梗图”，而sug词条“梗图抽象”中未包含明确的动词，无法识别其动作意图，因此动机匹配度为0。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”，sug词条仅提到“梗图”，且主体是泛化词“抽象”。sug词过度泛化，与原始问题核心对象“猫咪表情包”差距较大。作用域覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体内容和形式。sug词条「抽象」作为延伸词，与原始问题中的「双标行为」和「猫咪表情包」等具体内容无关，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "sug_梗图描改_r1_q8_6": {
      "type": "sug",
      "query": "[SUG] 梗图描改",
      "level": 13,
      "relevance_score": 0.192,
      "evaluationReason": "【评估对象】词条\"梗图描改\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成（猫咪表情包梗图）\n【动机维度 0.35】原始问题意图是「制作」梗图，sug词条「梗图描改」中的「描改」是制作梗图的一种具体方法或过程，「描改」与「制作」在动作意图上存在一定的关联性，属于弱相关。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”，sug词为“梗图描改”，sug词是制作梗图的一种方法，是制作层面的描述。主体词“梗图”匹配但缺乏其他限定，属于过度泛化，因此得分较低。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映人类双标行为」这一主题。sug词条「描改」是制作梗图的一种具体方法，但它没有提及「猫咪表情包」和「人类双标行为」这两个核心对象和主题，稀释了原始问题的聚焦度，使其偏离了核心需求。\n【最终得分 0.19】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_梗图模版_r1_q8_7": {
      "type": "sug",
      "query": "[SUG] 梗图模版",
      "level": 13,
      "relevance_score": 0.19400000000000003,
      "evaluationReason": "【评估对象】词条\"梗图模版\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/制作梗图\n【动机维度 0.00】原始问题询问的是如何“制作”梗图，包含明确的制作动作。sug词条“梗图模版”仅提供了制作梗图的辅助工具/对象，未能体现任何动作意图，因此动机匹配度为0。\n【品类维度 0.28】sug词条只包含对象层“梗图”，但原始问题的主体“猫咪双标行为表情包梗图”更为具体。sug词条只包含部分主体的泛化概念，缺失所有限定词，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调创意和内容。sug词条「梗图模版」作为延伸词，虽然与「梗图」相关，但它将用户的需求从「制作」具体内容的创意过程，稀释为对通用「模版」的寻找。这偏离了原始问题中「反映人类双标行为」和「猫咪表情包」的特定主题和创作目的，降低了内容的针对性。\n【最终得分 0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_梗图分享_r1_q8_8": {
      "type": "sug",
      "query": "[SUG] 梗图分享",
      "level": 13,
      "relevance_score": 0.085,
      "evaluationReason": "【评估对象】词条\"梗图分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题核心动机是“制作”，平台sug词条「梗图分享」的核心动机是“分享”，两者动机不匹配。sug词属于原始问题制作后的相关行为，但并非原始问题所需动机，故评分为0。\n【品类维度 0.25】sug词条《梗图分享》包含了原始问题中的核心对象《梗图》，但过度泛化且缺失了「反映人类双标行为的猫咪」这一所有限定词，匹配度一般。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条「梗图分享」将重点从「制作」转移到「分享」，且未提及「猫咪」或「双标行为」等核心对象和主题，稀释了原始问题的目的和聚焦度。\n【最终得分 0.09】",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.024
    },
    "sug_梗图大全_r1_q8_9": {
      "type": "sug",
      "query": "[SUG] 梗图大全",
      "level": 13,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图大全\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”，而sug词条“梗图大全”没有明确的动作意图。因此，sug词条与原始问题的动机不匹配。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”，sug词为“梗图大全”。sug词是原始问题对象层的过度泛化，只涵盖了通用对象，未提及核心对象“猫咪表情包”及其他限定词。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题「猫咪表情包梗图」，而sug词条「梗图大全」引入了与「制作」无关的「大全」概念，且未提及「猫咪表情包」和「双标行为」等核心对象，稀释了原始问题的聚焦度。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 1,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.024
    },
    "step_comb_r1": {
      "type": "step",
      "query": "步骤2: 域内组合 (15个组合)",
      "level": 11,
      "relevance_score": 0,
      "strategy": "域内组词",
      "iteration": 1,
      "is_selected": true
    },
    "comb_反映人类_r1_0": {
      "type": "domain_combination",
      "query": "反映人类",
      "level": 12,
      "relevance_score": 0.0702,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映人类\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.78 - 核心主体“反映人类”完全匹配，但限定词“双标行为”缺失，属于核心主体匹配，存在限定词匹配的情况。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.78 × 0.09\n【最终得分】0.07",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "人类"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "人类",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_反映双标_r1_1": {
      "type": "domain_combination",
      "query": "反映双标",
      "level": 12,
      "relevance_score": 0.081,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映双标\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.90 - 核心主体“双标”和限定词“反映”均匹配，但缺少了“人类行为”这一限定，因此给予高分但非满分。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.90 × 0.09\n【最终得分】0.08",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "双标"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "双标",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_反映行为_r1_2": {
      "type": "domain_combination",
      "query": "反映行为",
      "level": 12,
      "relevance_score": 0.0072,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.08 - sug词是通用概念“反映行为”，原始问题是特定概念“反映人类双标行为的”，通用概念不等于特定概念，因此品类不匹配，评分较低。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.08 × 0.09\n【最终得分】0.01",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": false,
      "max_source_score": 0.024,
      "scoreColor": "#ef4444"
    },
    "comb_人类双标_r1_3": {
      "type": "domain_combination",
      "query": "人类双标",
      "level": 12,
      "relevance_score": 0.081,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"人类双标\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.90 - 核心主体'人类双标'完全匹配，限定词'行为的'在词条中被省略，但语义上高度相关，属于合理泛化。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.90 × 0.09\n【最终得分】0.08",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "人类",
          "双标"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "人类",
              "score": 0.024
            },
            {
              "text": "双标",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_人类行为_r1_4": {
      "type": "domain_combination",
      "query": "人类行为",
      "level": 12,
      "relevance_score": 0.045,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"人类行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.50 - 核心主体'人类行为'匹配，但限定词'双标'缺失，属于合理泛化。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.50 × 0.09\n【最终得分】0.04",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "人类",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "人类",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_双标行为_r1_5": {
      "type": "domain_combination",
      "query": "双标行为",
      "level": 12,
      "relevance_score": 0.0765,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"双标行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.85 - 核心主体词“双标行为”完全匹配，但原始问题中包含“反映人类的”这一限定词，sug词未包含，因此略有缺失。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.85 × 0.09\n【最终得分】0.08",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "双标",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "双标",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_反映人类双标_r1_6": {
      "type": "domain_combination",
      "query": "反映人类双标",
      "level": 12,
      "relevance_score": 0.0882,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映人类双标\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.98 - 核心主体和限定词完全匹配，仅缺少一个助词，语义完全一致。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.98 × 0.09\n【最终得分】0.09",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "人类",
          "双标"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "人类",
              "score": 0.024
            },
            {
              "text": "双标",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_反映人类行为_r1_7": {
      "type": "domain_combination",
      "query": "反映人类行为",
      "level": 12,
      "relevance_score": 0.0702,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映人类行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.78 - 核心主体'人类行为'匹配，限定词'双标'在词条中缺失，但词条是同一作用域词条的合理泛化，因此给予较高分数。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.78 × 0.09\n【最终得分】0.07",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "人类",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "人类",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_反映双标行为_r1_8": {
      "type": "domain_combination",
      "query": "反映双标行为",
      "level": 12,
      "relevance_score": 0.0765,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映双标行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.85 - 核心主体“双标行为”匹配，限定词“反映”匹配，但缺少“人类”这一限定词，因此给予较高但非满分评分。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.85 × 0.09\n【最终得分】0.08",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "双标",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "双标",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_人类双标行为_r1_9": {
      "type": "domain_combination",
      "query": "人类双标行为",
      "level": 12,
      "relevance_score": 0.081,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"人类双标行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.90 - 核心主体“人类双标行为”完全匹配，但原始问题中的“反映”是动词，在品类维度评估中不予考虑，因此无法达到1.0分。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.90 × 0.09\n【最终得分】0.08",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "人类",
          "双标",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "人类",
              "score": 0.024
            },
            {
              "text": "双标",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_反映人类双标行为_r1_10": {
      "type": "domain_combination",
      "query": "反映人类双标行为",
      "level": 12,
      "relevance_score": 0.0882,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"反映人类双标行为\" vs 作用域\"反映人类双标行为的\"\n【品类得分】0.98 - 核心主体和限定词完全匹配，仅缺少一个助词，语义完全一致。\n【原始域得分】0.09\n【计算公式】品类得分 × 域得分 = 0.98 × 0.09\n【最终得分】0.09",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[修饰短语]",
      "source_words": [
        [
          "反映",
          "人类",
          "双标",
          "行为"
        ]
      ],
      "from_segments": [
        "反映人类双标行为的"
      ],
      "domains": [
        2
      ],
      "domains_str": "D2",
      "source_word_details": [
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            },
            {
              "text": "人类",
              "score": 0.024
            },
            {
              "text": "双标",
              "score": 0.024
            },
            {
              "text": "行为",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024,
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_猫咪表情包_r1_11": {
      "type": "domain_combination",
      "query": "猫咪表情包",
      "level": 12,
      "relevance_score": 0.21059999999999998,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"猫咪表情包\" vs 作用域\"猫咪表情包梗图\"\n【品类得分】0.90 - 核心主体“猫咪表情包”完全匹配，限定词“梗图”在词条中缺失，但“猫咪表情包”本身就常包含梗图，属于合理泛化，因此给予高分。\n【原始域得分】0.23\n【计算公式】品类得分 × 域得分 = 0.90 × 0.23\n【最终得分】0.21",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[中心名词]",
      "source_words": [
        [
          "猫咪",
          "表情包"
        ]
      ],
      "from_segments": [
        "猫咪表情包梗图"
      ],
      "domains": [
        3
      ],
      "domains_str": "D3",
      "source_word_details": [
        {
          "domain_index": 3,
          "segment_type": "中心名词",
          "segment_text": "猫咪表情包梗图",
          "words": [
            {
              "text": "猫咪",
              "score": 0.09
            },
            {
              "text": "表情包",
              "score": 0.15
            }
          ]
        }
      ],
      "source_scores": [
        0.09,
        0.15
      ],
      "is_above_sources": true,
      "max_source_score": 0.15,
      "scoreColor": "#22c55e"
    },
    "comb_猫咪梗图_r1_12": {
      "type": "domain_combination",
      "query": "猫咪梗图",
      "level": 12,
      "relevance_score": 0.21059999999999998,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"猫咪梗图\" vs 作用域\"猫咪表情包梗图\"\n【品类得分】0.90 - 核心主体“猫咪梗图”完全匹配，限定词“表情包”缺失，但“梗图”本身就包含“表情包”的含义，属于合理泛化。\n【原始域得分】0.23\n【计算公式】品类得分 × 域得分 = 0.90 × 0.23\n【最终得分】0.21",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[中心名词]",
      "source_words": [
        [
          "猫咪",
          "梗图"
        ]
      ],
      "from_segments": [
        "猫咪表情包梗图"
      ],
      "domains": [
        3
      ],
      "domains_str": "D3",
      "source_word_details": [
        {
          "domain_index": 3,
          "segment_type": "中心名词",
          "segment_text": "猫咪表情包梗图",
          "words": [
            {
              "text": "猫咪",
              "score": 0.09
            },
            {
              "text": "梗图",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.09,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.09,
      "scoreColor": "#22c55e"
    },
    "comb_表情包梗图_r1_13": {
      "type": "domain_combination",
      "query": "表情包梗图",
      "level": 12,
      "relevance_score": 0.1755,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"表情包梗图\" vs 作用域\"猫咪表情包梗图\"\n【品类得分】0.75 - 核心主体'表情包梗图'完全匹配，但限定词'猫咪'缺失，属于合理泛化。\n【原始域得分】0.23\n【计算公式】品类得分 × 域得分 = 0.75 × 0.23\n【最终得分】0.18",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[中心名词]",
      "source_words": [
        [
          "表情包",
          "梗图"
        ]
      ],
      "from_segments": [
        "猫咪表情包梗图"
      ],
      "domains": [
        3
      ],
      "domains_str": "D3",
      "source_word_details": [
        {
          "domain_index": 3,
          "segment_type": "中心名词",
          "segment_text": "猫咪表情包梗图",
          "words": [
            {
              "text": "表情包",
              "score": 0.15
            },
            {
              "text": "梗图",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.15,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.15,
      "scoreColor": "#22c55e"
    },
    "comb_猫咪表情包梗图_r1_14": {
      "type": "domain_combination",
      "query": "猫咪表情包梗图",
      "level": 12,
      "relevance_score": 0.23399999999999999,
      "evaluationReason": "【Round 1 域内评估】\n【评估对象】组合\"猫咪表情包梗图\" vs 作用域\"猫咪表情包梗图\"\n【品类得分】1.00 - 核心主体“猫咪表情包梗图”与所有关键限定词完全匹配，达到完美匹配。\n【原始域得分】0.23\n【计算公式】品类得分 × 域得分 = 1.00 × 0.23\n【最终得分】0.23",
      "strategy": "域内组合",
      "iteration": 1,
      "is_selected": true,
      "type_label": "[中心名词]",
      "source_words": [
        [
          "猫咪",
          "表情包",
          "梗图"
        ]
      ],
      "from_segments": [
        "猫咪表情包梗图"
      ],
      "domains": [
        3
      ],
      "domains_str": "D3",
      "source_word_details": [
        {
          "domain_index": 3,
          "segment_type": "中心名词",
          "segment_text": "猫咪表情包梗图",
          "words": [
            {
              "text": "猫咪",
              "score": 0.09
            },
            {
              "text": "表情包",
              "score": 0.15
            },
            {
              "text": "梗图",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.09,
        0.15,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.15,
      "scoreColor": "#22c55e"
    },
    "step_search_r1": {
      "type": "step",
      "query": "步骤3: 筛选并执行搜索 (筛选2个高分词，搜索2次，undefined个帖子)",
      "level": 11,
      "relevance_score": 0,
      "strategy": "筛选并执行搜索",
      "iteration": 1,
      "is_selected": true
    },
    "search_制作表情包_r1_0": {
      "type": "search_word",
      "query": "[SEARCH] 制作表情包",
      "level": 12,
      "relevance_score": 0.815,
      "strategy": "搜索词",
      "iteration": 1,
      "is_selected": true
    },
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      "query": "[R] 微信自制表情教程",
      "level": 23,
      "relevance_score": 0,
      "strategy": "帖子",
      "iteration": 2,
      "is_selected": true,
      "note_id": "66f9046a000000002a033202",
      "note_url": "https://www.xiaohongshu.com/explore/66f9046a000000002a033202",
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        "https://ci.xiaohongshu.com/1040g008318as11gc44504be7ut8lflqskgfuu80?imageView2/2/w/1080/format/webp",
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        "https://ci.xiaohongshu.com/1040g008318as11gc444g4be7ut8lflqshvdu428?imageView2/2/w/1080/format/webp",
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        "https://ci.xiaohongshu.com/1040g008318as11gc441g4be7ut8lflqsq87bfm0?imageView2/2/w/1080/format/webp",
        "https://ci.xiaohongshu.com/1040g008318as11gc44404be7ut8lflqsj8g29qo?imageView2/2/w/1080/format/webp"
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          "image_url": "https://ci.xiaohongshu.com/1040g008318as11gc441g4be7ut8lflqsq87bfm0?imageView2/2/w/1080/format/webp"
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          "image_url": "https://ci.xiaohongshu.com/1040g008318as11gc44404be7ut8lflqsj8g29qo?imageView2/2/w/1080/format/webp"
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        "collected_count": 1284,
        "comment_count": 201,
        "shared_count": 1262
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      "extraction": null,
      "is_knowledge": true,
      "knowledge_reason": "帖子提供了制作微信表情包的具体方法和步骤，包括利用现有表情和从图库添加图片制作，是可复用的创作教程。",
      "post_relevance_score": 0.5,
      "relevance_level": "中度相关",
      "relevance_reason": "帖子提供了制作表情包的通用方法，这对于制作猫咪表情包梗图是可复用的基础知识。但它没有直接涉及“反映人类双标行为”这一内容主题，也未提供具体的梗图创作技巧，因此是中度相关。"
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      "level": 23,
      "relevance_score": 0,
      "strategy": "帖子",
      "iteration": 2,
      "is_selected": true,
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      "note_url": "https://www.xiaohongshu.com/explore/668e06cd00000000250145fe",
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        "collected_count": 720,
        "comment_count": 108,
        "shared_count": 390
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      "is_knowledge": true,
      "knowledge_reason": "该帖子提供了将手机照片添加为微信表情包的具体操作步骤，包括菜单路径和添加方式，属于可复用的工具使用和流程指导。",
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      "level": 13,
      "relevance_score": 0,
      "strategy": "帖子",
      "iteration": 1,
      "is_selected": true,
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      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_表情包简笔画_r1_20": {
      "type": "next_round_item",
      "query": "[Q] 表情包简笔画",
      "level": 12,
      "relevance_score": 0.18,
      "strategy": "高增益SUG",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_双标图片_r1_21": {
      "type": "next_round_item",
      "query": "[Q] 双标图片",
      "level": 12,
      "relevance_score": 0.17,
      "strategy": "高增益SUG",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_表情包图片大全_r1_22": {
      "type": "next_round_item",
      "query": "[Q] 表情包图片大全",
      "level": 12,
      "relevance_score": 0.17,
      "strategy": "高增益SUG",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图meme_r1_23": {
      "type": "next_round_item",
      "query": "[Q] 梗图meme",
      "level": 12,
      "relevance_score": 0.17,
      "strategy": "高增益SUG",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图分享_r1_24": {
      "type": "next_round_item",
      "query": "[Q] 梗图分享",
      "level": 12,
      "relevance_score": 0.085,
      "strategy": "高增益SUG",
      "iteration": 1,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "round_2": {
      "type": "round",
      "query": "Round 2",
      "level": 20,
      "relevance_score": 0,
      "strategy": "第2轮",
      "iteration": 2,
      "is_selected": true
    },
    "step_sug_r2": {
      "type": "step",
      "query": "步骤1: 请求&评估推荐词 (179个)",
      "level": 21,
      "relevance_score": 0,
      "strategy": "请求&评估推荐词",
      "iteration": 2,
      "is_selected": true
    },
    "q_制作表情包_r2_0": {
      "type": "q",
      "query": "[Q] 制作表情包",
      "level": 22,
      "relevance_score": 0.815,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_制作表情包用什么软件_r2_q0_0": {
      "type": "sug",
      "query": "[SUG] 制作表情包用什么软件",
      "level": 23,
      "relevance_score": 0.31699999999999995,
      "evaluationReason": "【评估对象】词条\"制作表情包用什么软件\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.60】原始问题是“制作”表情包梗图，sug词条是“制作”表情包用什么软件。sug词条的动作意图和原始问题一致，且提供了实现原始问题中「制作」这一动作所需要的工具辅助信息\n【品类维度 0.08】原始问题关心的是制作特定主题的猫咪表情包梗图，sug词条「制作表情包用什么软件」对象层仅为「表情包」，无限定词，且过度泛化，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体内容和主题，而sug词条「制作表情包用什么软件」引入了「软件」这一工具维度。虽然软件是制作表情包的辅助工具，但它偏离了原始问题对内容和主题的关注，稀释了原始问题的聚焦度，属于作用域稀释型延伸词。\n【最终得分 0.32】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包微信_r2_q0_1": {
      "type": "sug",
      "query": "[SUG] 制作表情包微信",
      "level": 23,
      "relevance_score": 0.18,
      "evaluationReason": "【评估对象】词条\"制作表情包微信\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.35】原始问题的核心动机是学习「制作」表情包。sug词条「制作表情包微信」也包含「制作」的动作意图。虽然sug词条只涉及制作的「方式/平台」（微信），未能涵盖原始问题更具体的对象（反映人类双标行为的猫咪表情包梗图），但动作意图是相关的。\n【品类维度 0.05】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条仅包含「制作表情包」，在对象层上仅部分匹配，缺乏「猫咪」和「梗图」限定，场景层完全缺失。内容主体覆盖度低。\n【延伸词维度 -0.15】延伸词「微信」引入了平台限制，与原始问题中制作表情包的核心目的无关，稀释了用户对表情包制作方法和创意的关注，属于作用域稀释型。\n【最终得分 0.18】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包怎么赚钱_r2_q0_2": {
      "type": "sug",
      "query": "[SUG] 制作表情包怎么赚钱",
      "level": 23,
      "relevance_score": -0.17000000000000004,
      "evaluationReason": "【评估对象】词条\"制作表情包怎么赚钱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.15】原始问题的核心动机是“制作”表情包，sug词条的动机是“赚钱”。两者都包含了“表情包”这个对象，但原始问题关注制作，sug词条关注赚钱，动机方向不同，属于轻度偏离。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，限定词是“人类双标行为”；sug词条核心对象是“表情包”，限定词是“赚钱”。sug词条缺少原始核心对象“猫咪”和“梗图”，且限定词也完全不匹配，存在误导性。\n【延伸词维度 -0.15】sug词条「怎么赚钱」引入了原始问题未提及的商业化目的，稀释了原始问题「制作表情包」的创作和表达意图，属于作用域稀释型延伸词。\n【最终得分 -0.17】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包教程_r2_q0_3": {
      "type": "sug",
      "query": "[SUG] 制作表情包教程",
      "level": 23,
      "relevance_score": 0.6799999999999999,
      "evaluationReason": "【评估对象】词条\"制作表情包教程\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.95】原始问题的核心动机是「制作」表情包梗图，sug词条的动机也是「制作」表情包的「教程」，两者核心动作「制作」一致且sug词更加具象化为制作的教程，高度相关。\n【品类维度 0.05】原始问题对象层为“猫咪表情包梗图”，限定词为“反映人类双标行为”；sug词对象层为“表情包教程”，属于对象匹配但限定词缺失，通用度较高，评分较低。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题是关于“制作”表情包，sug词条“制作表情包教程”中的“教程”是对“制作”这一动机的细化，不属于延伸词。\n【最终得分 0.68】\n【规则说明】情况4：无延伸词，权重调整为 动机70% + 品类30%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包软件_r2_q0_4": {
      "type": "sug",
      "query": "[SUG] 制作表情包软件",
      "level": 23,
      "relevance_score": 0.192,
      "evaluationReason": "【评估对象】词条\"制作表情包软件\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题的核心动机是“制作”，sug词条“制作表情包软件”也包含了“制作”这一动作，但sug词条重心偏向于『制作所需工具』而非『制作内容或技巧』。虽然都是关于制作，但需求方向有差异，因此属于弱相关。\n【品类维度 0.08】原始问题核心对象是“猫咪表情包梗图”，限定词为“反映人类双标行为”；sug词是“制作表情包软件”。sug词过度泛化，仅包含原始问题中“制作”和“表情包”的泛化概念，缺失核心主体和所有限定词，匹配度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体内容创作，而sug词条「制作表情包软件」引入了工具维度，稀释了原始问题对内容和创意的关注，降低了聚焦度。\n【最终得分 0.19】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包gif_r2_q0_5": {
      "type": "sug",
      "query": "[SUG] 制作表情包gif",
      "level": 23,
      "relevance_score": 0.5599999999999999,
      "evaluationReason": "【评估对象】词条\"制作表情包gif\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.95】原始问题的核心动机是「制作表情包梗图」，sug词条「制作表情包gif」的核心动机是「制作表情包」，两者核心动作与意图高度一致。原始问题对『表情包』的使用场景和内容进行了限定，但sug词条仍然保留了核心的动机动作。gif是表情包的一种表现形式，因此属于具体化范畴。\n【品类维度 0.25】sug词条「制作表情包gif」包含了原始问题的核心对象层元素“制作表情包”，但缺失了核心修饰性对象“猫咪表情包”。sug词的范围更泛化，覆盖度较低。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的内容创作，而sug词条「gif」引入了新的格式维度，稀释了原始问题对内容和主题的关注，降低了聚焦度。\n【最终得分 0.56】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包动图_r2_q0_6": {
      "type": "sug",
      "query": "[SUG] 制作表情包动图",
      "level": 23,
      "relevance_score": 0.492,
      "evaluationReason": "【评估对象】词条\"制作表情包动图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.95】原始问题的核心动机是「制作」表情包梗图。sug词条的动机也是「制作」表情包动图。虽然一个是梗图一个是动图，但「制作」动作的语义高度一致，且都指向表情包。\n【品类维度 0.08】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条仅包含「表情包动图」这一泛化的对象，未提及具体主体「猫咪」及限定词「双标行为」。覆盖度极低。\n【延伸词维度 -0.15】原始问题聚焦于“梗图”这一静态或多格图片形式，而sug词条引入了“动图”这一新的表现形式，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.49】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_视频制作表情包_r2_q0_7": {
      "type": "sug",
      "query": "[SUG] 视频制作表情包",
      "level": 23,
      "relevance_score": 0.43,
      "evaluationReason": "【评估对象】词条\"视频制作表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.85】原始问题和sug词条的核心动作意图都是“制作表情包”，具有高度的匹配性。sug词提供了“视频”这种制作方式，是原始意图的子集或具体化场景。\n【品类维度 0.05】原始问题核心对象是《猫咪表情包梗图》，限定词有《人类双标行为》。sug词条核心对象是《表情包》，是原始问题核心对象的泛化，但完全缺失核心限定词，且存在对象错位（视频制作）。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，而sug词条引入了「视频」这一新的载体形式，稀释了原始问题对「梗图」这一特定形式的聚焦，降低了内容的针对性。\n【最终得分 0.43】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_美图秀秀制作表情包图片_r2_q0_8": {
      "type": "sug",
      "query": "[SUG] 美图秀秀制作表情包图片",
      "level": 23,
      "relevance_score": 0.43,
      "evaluationReason": "【评估对象】词条\"美图秀秀制作表情包图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.85】原始问题的核心动机是「制作」表情包梗图。sug词条明确提到了「制作」表情包图片，虽然对象、场景和目的有所差异，但核心制作动作是高度匹配的。\n【品类维度 0.05】原始问题对象层为《猫咪表情包梗图》，场景层为《反映人类双标行为》。sug词条对象层为《表情包图片》。对象层部分匹配。sug词条完全缺失所有场景层限定，对象层匹配度低，但属于相关品类，故分数较低。\n【延伸词维度 -0.15】延伸词“美图秀秀”和“图片”与原始问题“制作反映人类双标行为的猫咪表情包梗图”的核心目的和内容无关，引入了不必要的工具和通用概念，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.43】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "sug_制作表情包文字_r2_q0_9": {
      "type": "sug",
      "query": "[SUG] 制作表情包文字",
      "level": 23,
      "relevance_score": 0.44199999999999995,
      "evaluationReason": "【评估对象】词条\"制作表情包文字\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】用户想要「制作」表情包梗图，核心动作是创作或生成一个具体产物。\n【动机维度 0.85】原始问题的核心动机是「制作」表情包梗图，sug词条「制作表情包文字」的动词「制作」与原始问题完全一致，匹配度极高。尽管sug词条限定了制作「文字」，但「制作」这一核心动作和方向完全一致。\n【品类维度 0.08】原始问题核心对象层为「猫咪表情包梗图」，场景层包括「双标行为」和「人类」。sug词条「制作表情包文字」仅模糊包含「表情包」对象层，限定词「文字」与原始问题「梗图」有差异，主体元素大部分缺失。\n【延伸词维度 -0.15】延伸词「文字」与原始问题「猫咪表情包梗图」的核心对象不符，稀释了原始问题对图像和特定主题（猫咪、双标行为）的聚焦，降低了内容针对性。\n【最终得分 0.44】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.815
    },
    "q_表情包怎么制作_r2_1": {
      "type": "q",
      "query": "[Q] 表情包怎么制作",
      "level": 22,
      "relevance_score": 0.695,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_表情包怎么制作gif_r2_q1_0": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作gif",
      "level": 23,
      "relevance_score": 0.33,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作gif\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.65】原始问题核心动机是「制作」表情包，sug词条是「制作」gif。gif是表情包的常见形式，制作gif可以服务于制作表情包，二者动作意图高度相关。\n【品类维度 0.05】原始问题核心是「猫咪表情包梗图」这一特定类型内容。sug词仅有「表情包」这一泛化对象层，缺少核心限定词「猫咪」、「梗图」以及行为层面描述。二者品类存在代沟。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的内容和主题，而sug词条「gif」引入了无关的格式限定，稀释了原始问题的核心内容，属于作用域稀释型。\n【最终得分 0.33】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_表情包怎么制作动态_r2_q1_1": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作动态",
      "level": 23,
      "relevance_score": 0.272,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作动态\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题意图是「制作」反映特定主题的「梗图」，sug词条意图是「制作」能「动态」的「表情包」。两者核心动作「制作」一致，但sug词条具体化为「动态表情包」，原始问题则侧重「梗图」，并包含更复杂的表意需求，因此是弱相关。\n【品类维度 0.28】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「动态表情包制作」。Sug词条仅命中表情包，但限定词“动态”与原问题场景不符，且对象层缺失“猫咪”和“梗图”限定”。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」方法，并强调其「反映人类双标行为」这一主题。sug词条「动态」引入了新的制作形式，与原始问题中未提及的「动态」制作方式不符，稀释了原始问题对特定主题和内容的聚焦，属于作用域稀释型。\n【最终得分 0.27】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_表情包怎么制作微信_r2_q1_2": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作微信",
      "level": 23,
      "relevance_score": 0.31,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作微信\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.45】原始问题的核心动机是\"制作\"表情包。sug词条的动机也是\"制作\"表情包，但原始问题中的制作更加具体，指向制作梗图。两者都是制作表情包，但侧重点不同。\n【品类维度 0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条只涉及「表情包」这一部分对象，但缺少核心对象「猫咪」和所有限定词，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为的猫咪表情包梗图」的制作方法，而sug词条「微信」引入了新的平台限定，稀释了原始问题的核心内容，使其偏离了对表情包内容和主题的关注。\n【最终得分 0.31】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_表情包怎么制作文字_r2_q1_3": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作文字",
      "level": 23,
      "relevance_score": 0.455,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作文字\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.90】原始问题的核心动机是学习「制作」表情包梗图。sug词条「表情包怎么制作文字」的核心动机是学习「制作」表情包。两者的核心动作「制作」完全一致，只是sug词条限定了制作的内容为「文字」\n【品类维度 0.05】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「表情包」，无限定词。核心对象层部分匹配，但限定词全部缺失且语义错位。泛化相似。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「内容创意」（反映人类双标行为），而sug词条「文字」是表情包制作的通用元素，与原始问题特指的「猫咪」和「双标行为」内容无关，稀释了原始问题的核心内容和创意目的。\n【最终得分 0.46】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_小红书表情包怎么制作的_r2_q1_4": {
      "type": "sug",
      "query": "[SUG] 小红书表情包怎么制作的",
      "level": 23,
      "relevance_score": 0.0049999999999999906,
      "evaluationReason": "【评估对象】词条\"小红书表情包怎么制作的\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.20】原始问题意图是「制作」表情包梗图，sug词条意图是「制作」小红书表情包。两者都包含制作动作，但在制作对象上有差异，原始问题侧重意图表达，sug词条侧重平台属性，相关性较弱。\n【品类维度 -0.20】原始问题核心对象是《猫咪双标行为表情包梗图》，限定词有《人类双标行为》、《猫咪》。sug词条核心对象是《小红书表情包》，限定词是《小红书》。两者核心主体部分重合，但限定词完全不同，且《小红书》的限定范围无法涵盖《猫咪双标行为》。\n【延伸词维度 -0.15】延伸词“小红书”和“怎么制作的”与原始问题“反映人类双标行为的猫咪表情包梗图”的核心内容和目的不符。“小红书”引入了平台限定，稀释了原始问题对内容创作本身的关注；“怎么制作的”是通用制作方法，与原始问题中“反映人类双标行为的猫咪表情包梗图”的特定主题和创意需求无关，降低了内容的针对性。\n【最终得分 0.00】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_原创表情包怎么制作_r2_q1_5": {
      "type": "sug",
      "query": "[SUG] 原创表情包怎么制作",
      "level": 23,
      "relevance_score": 0.46699999999999997,
      "evaluationReason": "【评估对象】词条\"原创表情包怎么制作\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.90】原始问题的核心动机是\"制作表情包梗图\"，sug词条的动机是\"制作表情包\"。sug词条的动作\"制作\"与原始问题完全一致，属于高度匹配。\n【品类维度 0.08】原始问题对象层为「人类双标行为的猫咪表情包梗图」，场景层无。sug词条对象层为「原创表情包」。sug词条仅泛化匹配了部分对象（表情包），限定词「人类双标行为的猫咪」、「梗图」以及「原创」均未覆盖，覆盖度低，属于过度泛化。\n【延伸词维度 -0.15】sug词条「原创表情包怎么制作」中的“原创”和“怎么制作”属于原始问题作用域内的词汇，但“表情包”这一对象层面的词汇，与原始问题中的“反映人类双标行为的猫咪表情包梗图”相比，过于宽泛，稀释了原始问题中对“猫咪”和“双标行为”的特定要求，降低了内容的针对性。\n【最终得分 0.47】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_表情包怎么制作视频_r2_q1_6": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作视频",
      "level": 23,
      "relevance_score": 0.07999999999999997,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作视频\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.35】原始问题核心动机是「制作」表情包梗图，sug词条核心动机是「制作」视频。两者动作都是「制作」，但对象不同，一个针对表情包梗图，一个针对视频，属于弱相关。\n【品类维度 -0.20】原始问题需求的核心对象是「人类双标行为的猫咪表情包梗图」，涉及主题「双标行为」和主体「猫咪」，而sug词条仅提及「表情包」，且关注点是「制作视频」，与原始问题的主要对象、主题和形式均不匹配，存在误导性。\n【延伸词维度 -0.15】原始问题聚焦于「表情包梗图」的制作，而sug词条引入了「视频」这一延伸词。视频制作与梗图制作是两种不同的媒介和技能，稀释了原始问题对「梗图」的聚焦，降低了内容的针对性。\n【最终得分 0.08】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_表情包怎么制作动态图_r2_q1_7": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作动态图",
      "level": 23,
      "relevance_score": 0.21999999999999997,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作动态图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.35】原始问题的核心动机是「制作」表情包梗图。sug词条的动机也是「制作」表情包相关内容，但其侧重于「动态图」的制作，而非原始问题中「反映人类双标行为的猫咪表情包梗图」的特定内容制作，因此关联度较弱。\n【品类维度 0.15】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条对象层为「表情包」，场景层为「动态图」，两者对象层有部分重叠，但限定词偏差较大，且sug词条缺少猫咪的限定。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映双标行为」这一特定主题。sug词条「动态图」是制作方式的延伸，但原始问题并未提及对动态图的需求，且「动态图」的制作方式与「梗图」的制作方式可能存在差异，稀释了原始问题的核心目的和聚焦度。\n【最终得分 0.22】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_表情包怎么制作动图_r2_q1_8": {
      "type": "sug",
      "query": "[SUG] 表情包怎么制作动图",
      "level": 23,
      "relevance_score": 0.5599999999999999,
      "evaluationReason": "【评估对象】词条\"表情包怎么制作动图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.95】原始问题的核心动机是“制作”表情包梗图，Sug词条的核心动机是“制作”动图。动作上制作和制作完全匹配，仅对象存在差异，因此匹配度很高。\n【品类维度 0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「表情包」，场景层为「动图」。核心对象「表情包」匹配，但sug词缺失关键限定词「猫咪」、「梗图」，并有不匹配的限定词「动图」。\n【延伸词维度 -0.15】原始问题聚焦于“猫咪表情包梗图”这一特定内容，而延伸词“动图”引入了新的形式要求，稀释了对内容本身的关注，且与原始问题中的“梗图”概念不完全匹配，可能导致用户偏离创作核心。\n【最终得分 0.56】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "sug_制作表情包怎么赚钱_r2_q1_9": {
      "type": "sug",
      "query": "[SUG] 制作表情包怎么赚钱",
      "level": 23,
      "relevance_score": -0.17000000000000004,
      "evaluationReason": "【评估对象】词条\"制作表情包怎么赚钱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.15】原始问题的核心动机是“制作”表情包，sug词条的动机是“赚钱”。两者都包含了“表情包”这个对象，但原始问题关注制作，sug词条关注赚钱，动机方向不同，属于轻度偏离。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，限定词是“人类双标行为”；sug词条核心对象是“表情包”，限定词是“赚钱”。sug词条缺少原始核心对象“猫咪”和“梗图”，且限定词也完全不匹配，存在误导性。\n【延伸词维度 -0.15】sug词条「怎么赚钱」引入了原始问题未提及的商业化目的，稀释了原始问题「制作表情包」的创作和表达意图，属于作用域稀释型延伸词。\n【最终得分 -0.17】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.695
    },
    "q_双标表情包_r2_2": {
      "type": "q",
      "query": "[Q] 双标表情包",
      "level": 22,
      "relevance_score": 0.4,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_双标表情包内涵_r2_q2_0": {
      "type": "sug",
      "query": "[SUG] 双标表情包内涵",
      "level": 23,
      "relevance_score": 0.32000000000000006,
      "evaluationReason": "【评估对象】词条\"双标表情包内涵\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题明确意图是\"制作\"表情包，而sug词条\"双标表情包内涵\"聚焦于\"内涵\"这一主题，不包含制作这一动作意图，因此动机不匹配。\n【品类维度 0.40】原始问题对象层为「人类双标行为的猫咪表情包梗图」，场景层为「制作反映」。sug词条仅包含部分对象层「双标表情包」，核心主体和限定词有匹配但缺失「猫咪」限定和「梗图」限定，覆盖度较低。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“双标”和“表情包”在sug词条中被直接使用，而“内涵”可以视为对“反映”这一动机的细化或同义表达。\n【最终得分 0.32】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.4
    },
    "sug_双标表情包图片_r2_q2_1": {
      "type": "sug",
      "query": "[SUG] 双标表情包图片",
      "level": 23,
      "relevance_score": 0.48,
      "evaluationReason": "【评估对象】词条\"双标表情包图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是\"制作\"，而sug词条\"双标表情包图片\"是一个名词短语，没有包含任何动作意图，因此sug词条在此维度上缺失动作意图。\n【品类维度 0.60】sug词条「双标表情包图片」包含了原始问题中的核心对象「表情包」和限定词「双标」。缺失了对象「猫咪」和「梗图」。主体部分匹配，但限定词不完全。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“人类双标行为”被简化为“双标”，但核心概念未变；“猫咪表情包梗图”被简化为“表情包图片”，属于细化或同义词，不构成延伸。\n【最终得分 0.48】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.4
    },
    "sug_怼双标的人表情包_r2_q2_2": {
      "type": "sug",
      "query": "[SUG] 怼双标的人表情包",
      "level": 23,
      "relevance_score": 0.655,
      "evaluationReason": "【评估对象】词条\"怼双标的人表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.90】原始问题重点在“制作”表情包梗图，sug词条虽然是直接给出表情包，但不排除用户的制作意图，可以理解为寻找制作灵感或素材，因此动机一致。\n【品类维度 0.55】原始问题对象层为「猫咪表情包梗图」，场景层为「双标行为」。sug词条对象层为「表情包」，场景层为「怼双标的人」。对象层部分匹配（都为表情包），场景层部分匹配（都与双标相关）。内容主体有重叠。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，且主题是「人类双标行为」。sug词条「怼双标的人表情包」将「制作」这一核心动机替换为「怼」，且未提及「猫咪」，稀释了原始问题的核心目的和对象。\n【最终得分 0.66】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.4
    },
    "sug_可爱又双标的表情包_r2_q2_3": {
      "type": "sug",
      "query": "[SUG] 可爱又双标的表情包",
      "level": 23,
      "relevance_score": 0.68,
      "evaluationReason": "【评估对象】词条\"可爱又双标的表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），通过表情包梗图反映人类双标行为，主体是猫咪\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「可爱又双标的表情包」没有包含任何动作意图，因此动机匹配度为0。\n【品类维度 0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条对象层为「表情包」，场景层为「可爱又双标」。虽然未提及「猫咪」和「梗图」，但「双标」和「表情包」核心主体匹配，故属于部分场景层（双标）的匹配。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“猫咪”被“可爱”所概括，而“梗图”被“表情包”所概括，均属于同义词或细化词。\n【最终得分 0.68】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.4
    },
    "sug_讽刺双标的图片_r2_q2_4": {
      "type": "sug",
      "query": "[SUG] 讽刺双标的图片",
      "level": 23,
      "relevance_score": 0.49,
      "evaluationReason": "【评估对象】词条\"讽刺双标的图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（猫咪表情包梗图），这个表情包梗图需用于反映/讽刺人类双标行为，因此‘制作’是核心动机，‘反映/讽刺’是目的。\n【动机维度 0.00】原始问题意图是“制作”表情包梗图，而sug词条「讽刺双标的图片」是名词描述，无明确动作意图。sug词条未包含原始问题的核心动机。\n【品类维度 0.65】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词核心对象为「图片」，限定词为「讽刺双标」。其中「图片」是「梗图」的泛化，且「讽刺双标」与「反映人类双标行为」高度匹配，但缺失核心对象「猫咪」的限定。覆盖度较高，但有一定泛化和缺失，故给0.65分。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」这一特定形式，而sug词条「图片」泛化了对象，稀释了原始问题的具体性和趣味性，属于作用域稀释型。\n【最终得分 0.49】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.4
    },
    "sug_双标梗图模板_r2_q2_5": {
      "type": "sug",
      "query": "[SUG] 双标梗图模板",
      "level": 23,
      "relevance_score": 0.29000000000000004,
      "evaluationReason": "【评估对象】词条\"双标梗图模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 0.00】原始问题是「制作」反映人类双标行为的猫咪表情包梗图，sug词条是「双标梗图模板」。sug词条没有明确的动作，可以理解为学习、查看或获取模板，与原始问题的「制作」动作方向存在差异，因此动作方向上不匹配。考虑到sug词条本身无明确动机，得分为0。\n【品类维度 0.40】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条对象层为「梗图模板」，是原始问题对象层「梗图」的泛化且增加了「模板」限定，场景层为「双标」。主体匹配但限定有所泛化。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包」这一特定对象，而sug词条「模板」将范围扩大到所有「双标梗图」，稀释了原始问题的核心对象，降低了内容的针对性。\n【最终得分 0.29】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.4
    },
    "sug_讽刺双标的人的文案_r2_q2_6": {
      "type": "sug",
      "query": "[SUG] 讽刺双标的人的文案",
      "level": 23,
      "relevance_score": -0.14,
      "evaluationReason": "【评估对象】词条\"讽刺双标的人的文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.05】原始问题的核心动机是「制作」表情包梗图。sug词条的动机是「讽刺双标的人的文案」，这是一种「创作」行为或「寻找」行为，与原始问题的「制作」方向有轻微偏离。原始问题侧重行为主体，sug词条侧重内容主题。\n【品类维度 -0.25】原始问题核心对象是「猫咪表情包梗图」，场景限定为「人类双标行为」。sug词条核心对象为「文案」，场景限定为「讽刺双标的人」。对象错位，且场景限定差异较大。\n【延伸词维度 -0.15】原始问题聚焦于「制作猫咪表情包梗图」这一具体行为和对象，延伸词「文案」和「讽刺双标的人」偏离了制作表情包的动作和猫咪这一核心对象，稀释了原始问题的聚焦度。\n【最终得分 -0.14】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.4
    },
    "sug_很双标的朋友圈文案_r2_q2_7": {
      "type": "sug",
      "query": "[SUG] 很双标的朋友圈文案",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"很双标的朋友圈文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题核心动机是“制作”，sug词条“朋友圈文案”无明确动作意图，因此动机维度得分设为0。\n【品类维度 -0.20】原始问题核心是《猫咪表情包梗图》，限定词有《人类双标行为》。sug词条核心是《朋友圈文案》，限定词是《很双标》。sug与原始问题的主体“猫咪表情包梗图”完全不匹配，但限定词《双标》部分匹配，因此给予负分。\n【延伸词维度 -0.15】sug词条「朋友圈文案」与原始问题「猫咪表情包梗图」在内容形式上完全不符，且「朋友」与「人类」的范围差异，稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.4
    },
    "sug_这可是要砍头的表情包_r2_q2_8": {
      "type": "sug",
      "query": "[SUG] 这可是要砍头的表情包",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"这可是要砍头的表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成\n【动机维度 0.00】原始问题的核心动机是「制作/生成」，sug词条「这可是要砍头的表情包」仅是一句描述性短语，没有体现任何动作或意图。\n【品类维度 -0.20】原始问题核心是关于《人类双标行为》、《猫咪表情包》以及《梗图》的主体内容。平台sug词条仅包含《表情包》，且带有负面情绪限定，主体高度不匹配。\n【延伸词维度 -0.15】sug词条「这可是要砍头的表情包」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关的、具有误导性的信息，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.4
    },
    "sug_双标的人怎么怼_r2_q2_9": {
      "type": "sug",
      "query": "[SUG] 双标的人怎么怼",
      "level": 23,
      "relevance_score": -0.17500000000000004,
      "evaluationReason": "【评估对象】词条\"双标的人怎么怼\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「怎么怼」意图是「反击/对抗」。两者动作意图完全不匹配。\n【品类维度 -0.40】原始问题内容主体为「人类双标行为」和「猫咪表情包梗图」，sug词条内容主体为「双标的人」。sug只有「双标」相关概念，缺少「猫咪表情包梗图」这一核心对象，且sug词侧重于互动反驳，与原始问题制作内容的主体含义有较大差异，存在品类错位。\n【延伸词维度 -0.15】sug词条「双标的人怎么怼」中的“怼”是延伸词，它引入了与原始问题“制作表情包梗图”完全不相关的行为，稀释了原始问题的创作和表达目的，偏离了核心需求。\n【最终得分 -0.18】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.4
    },
    "q_梗图素材_r2_3": {
      "type": "q",
      "query": "[Q] 梗图素材",
      "level": 22,
      "relevance_score": 0.21000000000000002,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_梗图素材模板_r2_q3_0": {
      "type": "sug",
      "query": "[SUG] 梗图素材模板",
      "level": 23,
      "relevance_score": 0.084,
      "evaluationReason": "【评估对象】词条\"梗图素材模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是\"制作\"，而sug词条\"梗图素材模板\"不包含任何动作意图，因此动机维度评分为0。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”这一特定对象，sug词条“梗图素材模板”仅包含泛化的“梗图”对象，且限定词几乎为零，覆盖度极低。\n【延伸词维度 0.10】原始问题是制作梗图，sug词条中的“素材模板”是制作梗图的辅助工具，对原始问题有辅助作用，但非必需，属于作用域辅助型延伸词。\n【最终得分 0.08】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材抽象_r2_q3_1": {
      "type": "sug",
      "query": "[SUG] 梗图素材抽象",
      "level": 23,
      "relevance_score": 0.41000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图素材抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是\"制作\"梗图，而sug词条只提供了\"梗图素材\"，没有明确的动作意图。因此，sug词条缺失了动机层。\n【品类维度 0.55】原始问题核心对象是「猫咪表情包梗图」，限定词「反映人类双标行为」。sug词条核心对象「梗图素材」，限定词「抽象」。sug词条对象「梗图素材」与原始问题「猫咪表情包梗图」的主对象「梗图」匹配，但对象上缺失「猫咪表情包」限定词，限定词差异较大，故评为中等偏上匹配。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，强调了主题、对象和行为。sug词条「梗图素材抽象」中的「素材」和「抽象」是延伸词。「素材」属于作用域辅助型，对制作有辅助作用，但「抽象」与原始问题明确的「双标行为」主题相悖，稀释了原始问题的聚焦度，降低了内容的针对性，属于作用域稀释型。\n【最终得分 0.41】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材双人_r2_q3_2": {
      "type": "sug",
      "query": "[SUG] 梗图素材双人",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"梗图素材双人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图）\n【动机维度 0.00】sug词条「梗图素材双人」缺乏明确的动作意图。原始问题的核心动作是「制作」，sug词条虽然提及「梗图」，但无明确制作动作，因此无法评估动机匹配度。\n【品类维度 0.05】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词条「梗图素材双人」仅包含「梗图」这一核心对象的部分特征。内容主体匹配度极低，仅能弱关联。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，而sug词条「双人」引入了与原始问题对象不符的元素，稀释了对「猫咪」这一核心对象的关注，降低了内容的针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材单人_r2_q3_3": {
      "type": "sug",
      "query": "[SUG] 梗图素材单人",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图素材单人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图。sug词条“梗图素材单人”仅提供了制作梗图所需的部分对象（素材），但没有包含任何动机层信息，无法评估动机匹配度。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”和“双标行为”两个核心对象，sug词条仅包含“梗图”这一通用对象，且加入“单人”这一与原问题中“猫咪”和“双标行为”不符的限定，对象覆盖度极低并存在语义错位，为过度泛化。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调主题和内容。sug词条「素材」是制作梗图的辅助，但「单人」作为限定词，与原始问题中的「猫咪表情包」和「人类双标行为」的主题不符，稀释了原始问题的核心内容，降低了聚焦度。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材原图_r2_q3_4": {
      "type": "sug",
      "query": "[SUG] 梗图素材原图",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图素材原图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/反映\n【动机维度 0.00】原始问题的核心动机是“制作”和“反映”梗图，而sug词条“梗图素材原图”没有明确的动作意图，仅为名词短语，因此sug词条没有动机。\n【品类维度 0.08】原始问题的核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词条「梗图素材原图」是通用对象「梗图」的泛化概念。sug词只体现了对象层面的泛化，未包含任何重要限定词，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」这一具体创意过程。「梗图素材原图」中的「素材原图」是延伸词，它将原始问题从创意制作过程稀释为单纯的素材获取，降低了对核心创意和主题的关注度，属于作用域稀释型。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材多人_r2_q3_5": {
      "type": "sug",
      "query": "[SUG] 梗图素材多人",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图素材多人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.00】原始问题的核心动机是「制作」梗图，而sug词条「梗图素材多人」缺少明确的动作意图。sug词条提供了制作梗图的其中一个要素「素材」，但未体现「制作」这一核心动作，因此动机维度评分为0。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条核心对象为「梗图素材」，限定词「多人」。对象层部分匹配，但「多人」与「猫咪」限定词差异大且不相关，且缺乏「表情包」限定词，存在误导性。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，而延伸词「素材」虽然与制作相关，但「多人」限定词与原始问题中的「猫咪」对象不符，稀释了原始问题的核心对象，导致聚焦度下降。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材画画_r2_q3_6": {
      "type": "sug",
      "query": "[SUG] 梗图素材画画",
      "level": 23,
      "relevance_score": -0.23,
      "evaluationReason": "【评估对象】词条\"梗图素材画画\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「梗图素材画画」虽然包含「梗图」和「画画」可能指代制作过程，但没有明确表达制作的动作意图。\n【品类维度 -0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「梗图素材」「画画」，限定词缺失。两者主体类别差异大，且sug词过于泛化，关联性较低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条「素材画画」引入了与「制作」方式不符的「画画」这一延伸词，稀释了原始问题中「表情包梗图」的制作方式，降低了内容的针对性。\n【最终得分 -0.23】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材描改_r2_q3_7": {
      "type": "sug",
      "query": "[SUG] 梗图素材描改",
      "level": 23,
      "relevance_score": 0.07999999999999997,
      "evaluationReason": "【评估对象】词条\"梗图素材描改\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.35】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「梗图素材描改」包含了「梗图」和「描改」动作，描改是制作的子集动作，动机方向相关。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」；sug词是「梗图素材描改」，对象层面缺少「猫咪表情包」，且限定词均未覆盖。sug词仅能体现梗图的制作方式，而非内容主题。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的表情包梗图，强调「人类双标行为」和「猫咪」元素。「素材描改」作为延伸词，虽然与梗图制作相关，但它将原始问题从「制作」具体内容的层面，稀释到了「素材」和「描改」这种更基础、更宽泛的制作方法上，偏离了原始问题对内容和主题的聚焦，降低了针对性。\n【最终得分 0.08】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材表情包_r2_q3_8": {
      "type": "sug",
      "query": "[SUG] 梗图素材表情包",
      "level": 23,
      "relevance_score": 0.4,
      "evaluationReason": "【评估对象】词条\"梗图素材表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是“制作”表情包梗图，而sug词条「梗图素材表情包」没有明确的动作意图。\n【品类维度 0.50】原始问题的核心对象是“猫咪表情包梗图”，限定词为“反映人类双标行为”。sug词条“梗图素材表情包”包含了核心对象“梗图”和“表情包”，但缺失了“猫咪”这一关键限定词，且完全缺失了“反映人类双标行为”这一具体限定，故匹配度一般。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“表情包梗图”与sug词条中的“梗图素材表情包”在概念上是高度重合的，sug词条仅是对原始问题中对象层的重组和细化，不构成延伸。\n【最终得分 0.40】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21000000000000002
    },
    "sug_梗图素材聊天记录_r2_q3_9": {
      "type": "sug",
      "query": "[SUG] 梗图素材聊天记录",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"梗图素材聊天记录\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是“制作表情包梗图”。sug词条「梗图素材聊天记录」缺失了动作意图，只提供了制作梗图的其中一种材料“聊天记录”，无法识别动作，故动机维度得分为0。\n【品类维度 0.05】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「梗图素材」、「聊天记录」。Sug词条内容主体过度泛化，与原始问题的特定主体不匹配。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调创作过程和内容。sug词条「素材聊天记录」引入了「聊天记录」这一新的素材类型，与原始问题中「猫咪表情包」的核心对象不符，稀释了主题的聚焦度，降低了内容针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21000000000000002
    },
    "q_梗图模版_r2_4": {
      "type": "q",
      "query": "[Q] 梗图模版",
      "level": 22,
      "relevance_score": 0.19400000000000003,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_梗图模版抽象_r2_q4_0": {
      "type": "sug",
      "query": "[SUG] 梗图模版抽象",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图模版抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是“制作”梗图，而sug词条“梗图模版抽象”中没有明确的动作意图。\n【品类维度 0.08】原始问题是关于“猫咪表情包梗图”这一特定概念，sug词条“梗图模板抽象”是泛化的通用概念，仅包含核心对象“梗图”的抽象分类，缺失限定词和具体主体。因此匹配度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体内容创作，而sug词条「梗图模版抽象」引入了「模版」和「抽象」两个延伸词。这两个词与原始问题中的具体创作目标关联度较低，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版双人_r2_q4_1": {
      "type": "sug",
      "query": "[SUG] 梗图模版双人",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"梗图模版双人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题核心动机是「制作」反映人类双标行为的猫咪表情包梗图，sug词条「梗图模版双人」无明确的动作意图。\n【品类维度 0.05】原始问题涉及“猫咪表情包梗图”，sug词为“梗图模版双人”。sug词保留了不限定主体的“梗图”这一通用对象层，但丢失了核心对象《猫咪》和限定词《表情包》《双标行为》等，未明确体现《猫咪》主题，且增加了《双人》泛化限定词，造成语义错位。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映人类双标行为」这一主题。sug词条「梗图模版双人」中的「双人」是延伸词，它限定了梗图模版的人物数量，与原始问题中「猫咪表情包」和「人类双标行为」的主题不符，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版单人_r2_q4_2": {
      "type": "sug",
      "query": "[SUG] 梗图模版单人",
      "level": 23,
      "relevance_score": -0.23,
      "evaluationReason": "【评估对象】词条\"梗图模版单人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」反映特定主题的猫咪表情包梗图，sug词条「梗图模版单人」仅提及「梗图模版」，无法识别任何动作意图，因此动机维度得分设为0。\n【品类维度 -0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条对象层为「梗图模版」，场景层为「单人」。sug词仅有部分对象层匹配，无场景层匹配，且模版与特定主题梗图品类差距较大，有偏离性，故评为中低分。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映双标行为」这一特定主题。sug词条「梗图模版单人」中的「单人」是延伸词，它限制了梗图模版的使用场景，与原始问题中未限定的「猫咪表情包梗图」存在冲突，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.23】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模板_r2_q4_3": {
      "type": "sug",
      "query": "[SUG] 梗图模板",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】原始问题核心动机是“制作”表情包梗图。\n【动机维度 0.00】原始问题的核心动机是“制作”，sug词条“梗图模板”没有明确的动作意图，不涉及制作行为，因此动机维度评分为0。\n【品类维度 0.08】原始问题是关于《人类双标行为的猫咪表情包梗图》的具体制作，sug词条《梗图模板》过于泛化，只涵盖了梗图的通用概念，未提及猫咪、双标行为等核心要素，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体创意内容，而延伸词「模板」则将范围扩大到所有梗图，稀释了原始问题的核心创意和特定主题，降低了内容的针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版三人_r2_q4_4": {
      "type": "sug",
      "query": "[SUG] 梗图模版三人",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图模版三人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成（梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「梗图模版三人」没有明确的动作意图。因此，动机维度不匹配。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，限定词是“反映人类双标行为”；sug词条是“梗图模板三人”。sug词条只涵盖了“梗图”这一通用对象，且其限定词“三人”与原始问题的核心对象和限定词完全不符，存在品类错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和内容，而sug词条「梗图模版三人」中的「三人」是延伸词，它引入了与原始问题核心内容无关的限定条件，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版表情包_r2_q4_5": {
      "type": "sug",
      "query": "[SUG] 梗图模版表情包",
      "level": 23,
      "relevance_score": 0.33000000000000007,
      "evaluationReason": "【评估对象】词条\"梗图模版表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），通过描绘猫咪来反映人类双标行为，其核心意图是「制作」并传达「人类双标行为」\n【动机维度 0.00】原始问题核心动机是「制作」反映特定主题的梗图。sug词条「梗图模版表情包」本身是一个名词短语，不包含任何动作意图，因此无法与原始问题的动作意图匹配。\n【品类维度 0.45】原始问题对象层为“猫咪表情包梗图”，限定词为“反映人类双标行为”；sug词条对象层为“梗图模版表情包”，与原始问题主体部分匹配，但限定词全部缺失。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题（人类双标行为的猫咪表情包梗图），强调创意和内容。sug词条「梗图模版表情包」引入了「模版」这一延伸词，稀释了原始问题中「制作」的创意性和个性化需求，可能导致用户偏离原创制作，转而寻找现成模版，降低了内容的针对性。\n【最终得分 0.33】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版多人_r2_q4_6": {
      "type": "sug",
      "query": "[SUG] 梗图模版多人",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图模版多人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”梗图，而sug词条“梗图模版多人”没有明确的动作，无法评估动机匹配度。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，限定词为“反映人类双标行为”。Sug词条核心对象为“梗图模版”，限定词为“多人”。核心对象存在部分匹配（梗图），但限定词完全不匹配，且“模版”与“表情包”有差异，模版更具工具性。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作方法和主题「人类双标行为」，而sug词条「梗图模版多人」引入了「模版」和「多人」这两个延伸词。这两个延伸词与原始问题的主题和制作对象（猫咪表情包）关联度低，且「多人」与「猫咪」主题相悖，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版四人_r2_q4_7": {
      "type": "sug",
      "query": "[SUG] 梗图模版四人",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"梗图模版四人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（猫咪表情包梗图，反映人类双标行为）\n【动机维度 0.00】原始问题的核心动机是\"制作\"，sug词条\"梗图模版四人\"未包含任何显性或隐性的动作意图，无法评估动作匹配度。\n【品类维度 -0.20】原始问题是关于《猫咪表情包梗图》的制作，并限定了《人类双标行为》。sug词仅有《梗图》的主体，但限定词为《四人》，与原始问题《猫咪》、《人类双标行为》的内容主体完全不匹配，存在误导性。\n【延伸词维度 -0.15】sug词条「模版」和「四人」是延伸词。「模版」与原始问题中的「制作」有一定关联，但未明确指出是表情包模版，且「四人」与猫咪表情包的主题不符，稀释了原始问题的聚焦度。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_双眼皮模版图_r2_q4_8": {
      "type": "sug",
      "query": "[SUG] 双眼皮模版图",
      "level": 23,
      "relevance_score": -0.6760000000000002,
      "evaluationReason": "【评估对象】词条\"双眼皮模版图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的动机是“制作”表情包梗图，而sug词条「双眼皮模版图」无明确动机，侧重于“图”这一客体。\n【品类维度 -0.80】原始问题核心对象为「猫咪表情包梗图」及「双标行为」，sug词条「双眼皮模版图」与原始问题对象层和场景层均无任何关联，两者完全不属于同一品类，为严重的负向偏离。\n【延伸词维度 -0.18】sug词条「双眼皮模版图」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关信息，严重稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 -0.68】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "sug_梗图模版表格_r2_q4_9": {
      "type": "sug",
      "query": "[SUG] 梗图模版表格",
      "level": 23,
      "relevance_score": 0.07999999999999997,
      "evaluationReason": "【评估对象】词条\"梗图模版表格\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题意图是「制作表情包梗图」，sug词条「梗图模版表格」提供了制作梗图的辅助工具或资源，属于实现原始意图的间接相关动作。虽然sug词条本身无明确动作，但作为制作梗图的辅助途径，有弱相关性。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，sug词条是“梗图模板表格”。sug词条的“梗图”与核心对象部分匹配，但“模板”与“表格”限定词不符，且缺失核心实体“猫咪”，无法匹配原始问题主体形成有效匹配。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和内容，而sug词条「梗图模版表格」引入了与原始问题核心内容无关的「模版」和「表格」概念，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 0.08】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.19400000000000003
    },
    "q_梗图描改_r2_5": {
      "type": "q",
      "query": "[Q] 梗图描改",
      "level": 22,
      "relevance_score": 0.192,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_梗图描改接稿_r2_q5_0": {
      "type": "sug",
      "query": "[SUG] 梗图描改接稿",
      "level": 23,
      "relevance_score": -0.16500000000000004,
      "evaluationReason": "【评估对象】词条\"梗图描改接稿\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 -0.10】原始问题意图是「制作」梗图，sug词条「描改接稿」的「接稿」意在寻求制作服务，与用户「制作」意图方向略有偏差。\n【品类维度 -0.25】原始问题的核心对象是《人类双标行为的猫咪表情包梗图》，sug词的核心对象是《梗图描改接稿》，二者对象完全不匹配，品类冲突。\n【延伸词维度 -0.15】原始问题是关于「制作」特定主题的表情包梗图，而sug词条「描改接稿」引入了「描改」和「接稿」两个延伸词。这两个词与原始问题的「制作」行为不完全匹配，且「接稿」偏离了用户自主制作的意图，稀释了原始问题的聚焦度。\n【最终得分 -0.17】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_梗图描改素材_r2_q5_1": {
      "type": "sug",
      "query": "[SUG] 梗图描改素材",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"梗图描改素材\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图。sug词条「梗图描改素材」主要指示获取素材，没有体现出「制作」的动作意图。\n【品类维度 0.08】原始问题是关于『猫咪表情包梗图』，sug词『梗图描改素材』，原始问题具有很强的特定性，sug词泛化，只存在概念上的父子关系，因此得分很低\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体创意和内容，而sug词条「描改素材」则将重点转移到素材的获取和修改上。这稀释了原始问题中关于「双标行为」、「猫咪表情包」等核心创意和主题的关注度，降低了内容的针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_梗图描改教程_r2_q5_2": {
      "type": "sug",
      "query": "[SUG] 梗图描改教程",
      "level": 23,
      "relevance_score": 0.705,
      "evaluationReason": "【评估对象】词条\"梗图描改教程\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（梗图）\n【动机维度 0.90】原始问题的核心动机是「制作」梗图。sug词条中的「描改」是制作梗图的一种具体方法或技巧，属于制作行为的一部分，动机高度相关。\n【品类维度 0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条仅提及「梗图」，对象层匹配度低，场景层缺失，覆盖度低。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题是关于制作梗图，sug词条的“梗图”和“教程”均属于原始问题的作用域。\n【最终得分 0.70】\n【规则说明】情况4：无延伸词，权重调整为 动机70% + 品类30%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.192
    },
    "sug_梗图描改怎么画_r2_q5_3": {
      "type": "sug",
      "query": "[SUG] 梗图描改怎么画",
      "level": 23,
      "relevance_score": 0.105,
      "evaluationReason": "【评估对象】词条\"梗图描改怎么画\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.40】原始问题意图是“制作”猫咪表情包梗图，sug词条意图是“画（梗图）”，两者都指代制作梗图，是相关的行为。但sug词条中包含“描改”这一具体方法，只是制作的一种，因此是相关但在方法层面有差异。\n【品类维度 -0.20】原始问题的核心内容主体是「猫咪表情包梗图」，限定词是「人类双标行为」。Sug词条是「梗图描改」，对象层面通用，未提及核心内容主体的限定词，更侧重制作方法，品类差异较大。\n【延伸词维度 -0.15】原始问题聚焦于「制作猫咪表情包梗图」这一特定主题，并强调「反映人类双标行为」。sug词条「描改怎么画」引入了「描改」这一新的制作方式，且未提及猫咪或双标行为，稀释了原始问题的核心主题和目的，属于作用域稀释型。\n【最终得分 0.10】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_梗图描改模板_r2_q5_4": {
      "type": "sug",
      "query": "[SUG] 梗图描改模板",
      "level": 23,
      "relevance_score": 0.28500000000000003,
      "evaluationReason": "【评估对象】词条\"梗图描改模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.40】原始问题意图是「制作」表情包梗图，而sug词条「梗图描改模板」虽然与「梗图」主题相关，但其核心动作是「描改模板」，与「制作」存在一定差异，描改是制作的辅助操作，所以相关联，但并非直接匹配。\n【品类维度 0.25】原始问题核心对象是《猫咪表情包梗图》，限定词是《人类双标行为》。sug词条《梗图描改模板》只包含了核心对象《梗图》，但完整度一般，没有包含任何限定词。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和内容。sug词条「描改模板」虽然与「制作」行为相关，但它将原始问题限定在「描改」这一具体方法上，且未提及「猫咪表情包」或「双标行为」等核心内容，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 0.29】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.192
    },
    "sug_梗图描改约稿_r2_q5_5": {
      "type": "sug",
      "query": "[SUG] 梗图描改约稿",
      "level": 23,
      "relevance_score": 0.0050000000000000044,
      "evaluationReason": "【评估对象】词条\"梗图描改约稿\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是\"制作\"表情包梗图。sug词条「梗图描改约稿」中的「描改」和「约稿」是两种不同行为，描改可以理解为二次创作或制作的一种方式，但「约稿」是委托他人制作。sug词条未聚焦于\"制作\"，且引入了新动作「约稿」，并非核心动作。\n【品类维度 0.05】sug词条只涵盖了与原始问题相关的“梗图”这一通用对象层元素，情感色彩和主要意图与原始问题不符。原始问题更具体，要求猫咪表情包和双标行为，而sug词条未提及，造成巨大的限定词义偏差。\n【延伸词维度 -0.15】原始问题是关于“制作”特定主题的表情包梗图，强调的是创作过程和内容。sug词条中的“描改”和“约稿”是与“制作”相关的行为，但“约稿”引入了商业或委托的维度，稀释了原始问题中可能包含的个人创作或学习制作的意图。同时，“描改”是制作梗图的一种方式，但并非唯一方式，且原始问题未限定制作方式。因此，这些延伸词对原始问题的作用域有轻微稀释作用。\n【最终得分 0.01】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_梗图描改原图_r2_q5_6": {
      "type": "sug",
      "query": "[SUG] 梗图描改原图",
      "level": 23,
      "relevance_score": 0.15499999999999997,
      "evaluationReason": "【评估对象】词条\"梗图描改原图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.50】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图，sug词条是「梗图描改原图」，「描改」是「制作」梗图的一种具体方法，所以动作意图相关。\n【品类维度 -0.20】原始问题核心对象是《猫咪表情包梗图》，限定词包括《人类双标行为》。sug词条核心对象为《梗图》，但限定词《描改原图》与原始问题对象的核心属性和限定词均不匹配，存在偏离。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和创意，而sug词条「描改原图」则是一个通用的制作方法，与原始问题的核心创意和主题无关，稀释了原始问题的聚焦度。\n【最终得分 0.15】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_梗图描改鸡蛋_r2_q5_7": {
      "type": "sug",
      "query": "[SUG] 梗图描改鸡蛋",
      "level": 23,
      "relevance_score": -0.04000000000000002,
      "evaluationReason": "【评估对象】词条\"梗图描改鸡蛋\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图。Sug词条是「梗图描改鸡蛋」，其中「梗图」与原始问题「梗图」有表面关联，但「描改」并非原始问题的「制作」。两者均涉及动作「制作」/「描改」。sug词条中的「描改」是制作的一种方式，但对象「鸡蛋」与原始问题「猫咪表情包」完全不相关。因此，动机相关但偏离。\n【品类维度 -0.50】原始问题核心对象为「猫咪表情包梗图」与「人类双标行为」，sug词条为「梗图」和「鸡蛋」。两者核心对象「猫咪表情包」和「鸡蛋」完全不匹配，差异悬殊。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映双标行为」这一主题。sug词条「描改鸡蛋」引入了与原始问题主题无关的「鸡蛋」元素，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.04】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_抽象梗图描改_r2_q5_8": {
      "type": "sug",
      "query": "[SUG] 抽象梗图描改",
      "level": 23,
      "relevance_score": 0.192,
      "evaluationReason": "【评估对象】词条\"抽象梗图描改\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题核心动机是制作梗图，sug词条「抽象梗图描改」包含『梗图』，且『描改』是一种制作梗图的动作。描改和制作有相关性，但不是完全一致或强相关，属于弱相关。\n【品类维度 0.08】原始问题需求“猫咪表情包梗图”这一特定对象，且“反映人类双标行为”是其场景限定。sug词条“抽象梗图描改”是抽象泛化的概念，虽有“梗图”，但核心词“描改”与原始问题的“制作”有区别，且未提及“猫咪”和“双标行为”的限定，覆盖度极低。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」和「人类双标行为」的结合，而sug词条「抽象梗图描改」中的「抽象」和「描改」与原始问题中的核心对象和动机关联度较低，稀释了原始问题的聚焦度。\n【最终得分 0.19】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.192
    },
    "sug_梗图描改过程_r2_q5_9": {
      "type": "sug",
      "query": "[SUG] 梗图描改过程",
      "level": 23,
      "relevance_score": 0.46,
      "evaluationReason": "【评估对象】词条\"梗图描改过程\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 0.55】原始问题是「制作」梗图，sug词条是「梗图描改过程」。「描改过程」是制作梗图的一种具体方法或步骤，属于制作子集，动机相关。\n【品类维度 0.50】原始问题核心对象为「猫咪表情包梗图」，sug词条核心对象为「梗图描改过程」。「梗图」部分匹配，但sug词条未提及「猫咪表情包」及内容限定「人类双标行为」。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和内容，而sug词条「描改过程」虽然是制作梗图的一种方法，但它稀释了原始问题中「人类双标行为」和「猫咪表情包」这两个核心内容限定，使其偏离了原始问题的核心目的和聚焦度，属于作用域稀释型。\n【最终得分 0.46】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.192
    },
    "q_表情包简笔画_r2_6": {
      "type": "q",
      "query": "[Q] 表情包简笔画",
      "level": 22,
      "relevance_score": 0.18,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_表情包简笔画可爱_r2_q6_0": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画可爱",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包简笔画可爱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”特定主题的表情包梗图。平台sug词条“表情包简笔画可爱”未包含任何动作意图，因此动机匹配度为0。\n【品类维度 -0.20】原始问题核心对象层为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条「表情包简笔画可爱」包含对象「表情包」，但此表情包带有「简笔画」「可爱」的限定词，与原始问题中的「猫咪」「梗图」「双标行为」完全不匹配，且存在明显的风格偏差，属于品类错位。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的制作，强调内容和主题。sug词条「简笔画可爱」引入了绘画风格和情感倾向，与原始问题的内容和主题关联度较低，稀释了原始问题的核心目的，属于作用域稀释型。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画抽象_r2_q6_1": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画抽象",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包简笔画抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「表情包简笔画抽象」中没有明确的动作意图。sug词条无法识别动作，因此无法评估动作匹配度。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。Sug词条为「表情包简笔画抽象」，核心对象是「表情包简笔画」，限定词是「抽象」。sug词条未提及猫咪、梗图及双标行为限定，且简笔画与原始需求的「梗图」差异较大，内容主体错位。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，强调「人类双标行为」这一主题。sug词条「简笔画」和「抽象」引入了与原始问题制作主题和风格不符的元素，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画大全_r2_q6_2": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画大全",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包简笔画大全\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「表情包简笔画大全」无明确的动作意图，因此无法评估动作匹配度。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。Sug词条为「表情包简笔画大全」，虽包含「表情包」，但限定词「简笔画大全」与原始问题完全不符且无「猫咪」主体词，品类有较大偏差。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的特定主题制作。sug词条「简笔画大全」引入了与原始问题主题和目的无关的绘画风格和内容，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画哭_r2_q6_3": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画哭",
      "level": 23,
      "relevance_score": -0.3500000000000001,
      "evaluationReason": "【评估对象】词条\"表情包简笔画哭\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图\n【动机维度 0.00】原始问题的核心动机是「制作」梗图，sug词条「表情包简笔画哭」没有明确的动作意图。\n【品类维度 -0.40】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词条核心对象为「表情包」，限定词为「简笔画哭」。sug词条与原始问题仅对象「表情包」有部分重叠，限定词和更具体的对象描述完全不同且品类错位，关联度低。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的制作，强调主题和内容。sug词条「简笔画哭」引入了绘画风格和情绪，与原始问题的核心主题和制作目的关联度较低，稀释了原始问题的聚焦度。\n【最终得分 -0.35】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画图片_r2_q6_4": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画图片",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"表情包简笔画图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图，sug词条「表情包简笔画图片」没有明确的动作意图。虽然对象都和「表情包」相关，但sug词条中无动机层，无法评估动机维度匹配度。\n【品类维度 0.05】原始问题需求「猫咪表情包梗图」，侧重主题和内容。sug词条「表情包简笔画图片」仅部分覆盖了核心对象词「表情包」，但错失了核心限定词。简笔画与原始需求关联度较低。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的特定主题制作。sug词条「简笔画图片」引入了与原始问题主题无关的绘画风格和图片类型，稀释了原始问题的核心内容和目的，属于作用域稀释型延伸词。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画人物_r2_q6_5": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画人物",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包简笔画人物\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「表情包简笔画人物」没有明确的动作意图。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词核心对象为「简笔画人物」和「表情包」，对象虽有重叠但「人物」和「猫咪」冲突，且缺失所有限定词，语义偏离。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」和「人类双标行为」的结合，而sug词条「简笔画人物」引入了与原始问题核心对象「猫咪」和主题「双标行为」无关的绘画风格和对象，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画教程_r2_q6_6": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画教程",
      "level": 23,
      "relevance_score": 0.18,
      "evaluationReason": "【评估对象】词条\"表情包简笔画教程\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.35】原始问题的核心动机是「制作」表情包梗图。sug词条的动机亦为「制作/教程」，两者在制作层面是相关的，但sug词条「简笔画」并未完全涵盖原始问题的表情包梗图，因此是弱相关。\n【品类维度 0.05】原始问题涉及“猫咪表情包梗图”和“人类双标行为”两个主要内容主体；sug词只提及“表情包”，缺失核心对象“猫咪”及所有限定词，且存在对象错位（猫咪vs简笔画）\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的特定主题创作，而sug词条「简笔画教程」引入了与原始问题主题和目的关联度较低的绘画技巧，稀释了创作主题的聚焦性，属于作用域稀释型。\n【最终得分 0.18】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情简笔画_r2_q6_7": {
      "type": "sug",
      "query": "[SUG] 表情简笔画",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"表情简笔画\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「表情简笔画」中没有明确的动作意图。sug词条提供了制作表情包的一种「素材」或「风格」，但未展现制作的动作，因此动机维度评分为0。\n【品类维度 0.05】原始问题涉及「猫咪表情包梗图」，而sug词条是「表情简笔画」。两者主题在「表情」上有轻微关联，但猫咪、梗图、双标行为等核心限定都没有体现，匹配度低。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映双标行为」这一特定主题。sug词条「简笔画」作为一种绘画风格，与原始问题中的「猫咪表情包梗图」制作方法相关，但其过于宽泛，且未提及「猫咪」和「双标行为」的核心要素，稀释了原始问题的核心目的和聚焦度，属于作用域稀释型。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画加油_r2_q6_8": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画加油",
      "level": 23,
      "relevance_score": -0.09500000000000001,
      "evaluationReason": "【评估对象】词条\"表情包简笔画加油\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】sug词条「表情包简笔画加油」的动机是“简笔画（表情包）”或“给表情包加油”，与原始问题“制作表情包梗图”的动机“制作”无关，方向不一致。\n【品类维度 -0.20】原始问题涉及「猫咪表情包梗图」这一核心主体。Sug词条仅有「表情包」与核心主体部分匹配，但增加了「简笔画」「加油」等限定词，与原始问题完全不匹配，甚至存在语义错位。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的制作，强调主题和内容。sug词条「简笔画」和「加油」与原始问题的核心主题和制作目的无关，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.10】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "sug_表情包简笔画开心_r2_q6_9": {
      "type": "sug",
      "query": "[SUG] 表情包简笔画开心",
      "level": 23,
      "relevance_score": -0.09500000000000001,
      "evaluationReason": "【评估对象】词条\"表情包简笔画开心\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图，表达含义\n【动机维度 0.00】原始问题意图是“制作”具有特定内涵的表情包梗图，sug词条「表情包简笔画开心」侧重“绘画”这一动作，并且没有明确的情绪表达目的，无法匹配，故得分为0。\n【品类维度 -0.20】原始问题核心对象为「人类双标行为的猫咪表情包梗图」。sug词条「表情包简笔画开心」对象为「表情包」，但限定词与原始问题无关且对象带有「简笔画」属性，与要求不符。\n【延伸词维度 -0.15】sug词条「简笔画」和「开心」与原始问题「反映人类双标行为的猫咪表情包梗图」的核心目的和主题不符，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.10】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.18
    },
    "q_双标图片_r2_7": {
      "type": "q",
      "query": "[Q] 双标图片",
      "level": 22,
      "relevance_score": 0.17,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_讽刺双标的图片_r2_q7_0": {
      "type": "sug",
      "query": "[SUG] 讽刺双标的图片",
      "level": 23,
      "relevance_score": 0.49,
      "evaluationReason": "【评估对象】词条\"讽刺双标的图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（猫咪表情包梗图），这个表情包梗图需用于反映/讽刺人类双标行为，因此‘制作’是核心动机，‘反映/讽刺’是目的。\n【动机维度 0.00】原始问题意图是“制作”表情包梗图，而sug词条「讽刺双标的图片」是名词描述，无明确动作意图。sug词条未包含原始问题的核心动机。\n【品类维度 0.65】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词核心对象为「图片」，限定词为「讽刺双标」。其中「图片」是「梗图」的泛化，且「讽刺双标」与「反映人类双标行为」高度匹配，但缺失核心对象「猫咪」的限定。覆盖度较高，但有一定泛化和缺失，故给0.65分。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」这一特定形式，而sug词条「图片」泛化了对象，稀释了原始问题的具体性和趣味性，属于作用域稀释型。\n【最终得分 0.49】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "sug_暗示双标的图片_r2_q7_1": {
      "type": "sug",
      "query": "[SUG] 暗示双标的图片",
      "level": 23,
      "relevance_score": 0.24999999999999997,
      "evaluationReason": "【评估对象】词条\"暗示双标的图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「暗示双标的图片」中不包含明确的动作意图，因此无法评估动作匹配度。\n【品类维度 0.35】sug词条只包含了原始问题中的【双标】和【图】两个核心概念，缺失了特指的【猫咪表情包】。sug词条范围过于宽泛，导致内容主体性匹配度不高。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」这一特定形式，而sug词条「暗示双标的图片」将范围扩大到所有图片，稀释了原始问题的核心对象「猫咪表情包梗图」，降低了内容的针对性。\n【最终得分 0.25】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "sug_双标搞笑图片_r2_q7_2": {
      "type": "sug",
      "query": "[SUG] 双标搞笑图片",
      "level": 23,
      "relevance_score": 0.29000000000000004,
      "evaluationReason": "【评估对象】词条\"双标搞笑图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】sug词条《双标搞笑图片》无明确动作意图，只包含对象和场景信息，无法评估其动作匹配度。\n【品类维度 0.40】原始问题对象层为「猫咪表情包梗图」和「人类双标行为」，场景层无。Sug词条包含「双标」和「图片」，与原始问题中的核心要素有部分重合，但缺失「猫咪」和「梗图」的特定性。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」的制作，强调「人类双标行为」这一主题。sug词条「搞笑图片」虽然与「梗图」有一定关联，但缺少了「猫咪」和「表情包」这两个核心对象，且「制作」的动机也未体现，稀释了原始问题的具体性和目的性。\n【最终得分 0.29】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "sug_讽刺双标的人的文案_r2_q7_3": {
      "type": "sug",
      "query": "[SUG] 讽刺双标的人的文案",
      "level": 23,
      "relevance_score": -0.14,
      "evaluationReason": "【评估对象】词条\"讽刺双标的人的文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 -0.05】原始问题的核心动机是「制作」表情包梗图。sug词条的动机是「讽刺双标的人的文案」，这是一种「创作」行为或「寻找」行为，与原始问题的「制作」方向有轻微偏离。原始问题侧重行为主体，sug词条侧重内容主题。\n【品类维度 -0.25】原始问题核心对象是「猫咪表情包梗图」，场景限定为「人类双标行为」。sug词条核心对象为「文案」，场景限定为「讽刺双标的人」。对象错位，且场景限定差异较大。\n【延伸词维度 -0.15】原始问题聚焦于「制作猫咪表情包梗图」这一具体行为和对象，延伸词「文案」和「讽刺双标的人」偏离了制作表情包的动作和猫咪这一核心对象，稀释了原始问题的聚焦度。\n【最终得分 -0.14】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_双标梗_r2_q7_4": {
      "type": "sug",
      "query": "[SUG] 双标梗",
      "level": 23,
      "relevance_score": 0.27999999999999997,
      "evaluationReason": "【评估对象】词条\"双标梗\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】sug词条「双标梗」是名词短语，无法识别出明确的动作意图，因此无法与原始问题的动作「制作」进行动机匹配，得分为0。\n【品类维度 0.35】原始问题涉及“双标行为”和“梗图”，Sug词条包含“双标梗”，对象层有部分匹配，但缺失了核心的“猫咪表情包”限定，覆盖度较低。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。\n【最终得分 0.28】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "sug_双标是什么意思_r2_q7_5": {
      "type": "sug",
      "query": "[SUG] 双标是什么意思",
      "level": 23,
      "relevance_score": 0.0050000000000000044,
      "evaluationReason": "【评估对象】词条\"双标是什么意思\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】「制作」猫咪表情包梗图，用于「反映」人类双标行为。核心动作是「制作」和「反映」\n【动机维度 0.00】原始问题的核心动机是「制作」和「反映」。sug词条「双标是什么意思」的核心动机是「了解/理解」。sug词条仅包含原始问题的主题「双标」，但没有围绕原始问题的核心动作「制作」或「反映」提供任何动机支持，因此动机不匹配。\n【品类维度 0.05】原始问题核心是《猫咪表情包梗图制作》，限定词是《人类双标行为》。sug词条仅包含《双标》，与原始问题的核心对象层《猫咪表情包梗图》几乎无关，覆盖度极低。\n【延伸词维度 -0.15】sug词条「双标是什么意思」中的「是什么意思」是延伸词，它将原始问题从「制作」行为转移到「解释」概念，稀释了原始问题制作梗图的聚焦度，降低了内容针对性。\n【最终得分 0.01】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_形容双标人的文案_r2_q7_6": {
      "type": "sug",
      "query": "[SUG] 形容双标人的文案",
      "level": 23,
      "relevance_score": -0.09500000000000001,
      "evaluationReason": "【评估对象】词条\"形容双标人的文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图，表达双标行为\n【动机维度 0.00】原始问题的动机是「制作」反映双标行为的表情包梗图，sug词条的动机是「形容」双标人的文案。原始问题与sug词条的动作意图完全不同，动机不匹配。\n【品类维度 -0.20】原始问题核心是《猫咪表情包梗图》，sug词条是《文案》，品类完全不匹配。原始问题包含《双标行为/人》的限定，sug词条包含《双标人》的限定，限定词部分重合，但主体偏差大，且sug词条无法涵盖原始问题核心对象。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，而sug词条「形容双标人的文案」将主题从制作行为和猫咪表情包转移到文案本身，且与「梗图」的视觉表达形式不符，稀释了原始问题的核心目的和对象。\n【最终得分 -0.10】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_内涵双标的文案_r2_q7_7": {
      "type": "sug",
      "query": "[SUG] 内涵双标的文案",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"内涵双标的文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/创造反映人类双标行为的猫咪表情包梗图\n【动机维度 0.00】原始问题的核心动机是\"制作\"带有特定主题（双标行为）的图片内容，而sug词条是\"内涵\"（理解/包含）某种文案。sug词条无明确动作意图\n【品类维度 0.05】原始问题核心对象是《猫咪表情包梗图》，次要对象是《人类双标行为》，sug词条仅包含《双标》这一核心名词，未包含完整的对象层核心词和所有限定词，且存在语义错位。\n【延伸词维度 -0.15】原始问题聚焦于制作「猫咪表情包梗图」以反映「人类双标行为」，而sug词条「内涵双标的文案」将重点从「猫咪表情包梗图」转移到「文案」，且未提及「猫咪」或「表情包」，稀释了原始问题的核心对象和目的，属于作用域稀释型。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_卡皮巴拉100种可爱图片_r2_q7_8": {
      "type": "sug",
      "query": "[SUG] 卡皮巴拉100种可爱图片",
      "level": 23,
      "relevance_score": -0.56,
      "evaluationReason": "【评估对象】词条\"卡皮巴拉100种可爱图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条“卡皮巴拉100种可爱图片”没有任何动作或动机。sug词条不包含动作意图，因此动机匹配度为0。\n【品类维度 -0.55】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」；sug词条对象层为「卡皮巴拉图片」，场景层为「可爱」。二者核心对象和限定词完全不匹配，品类冲突。\n【延伸词维度 -0.60】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，核心是「猫咪表情包」和「双标行为」的结合，以及「制作」这一动作。sug词条「卡皮巴拉100种可爱图片」引入了「卡皮巴拉」这一全新的对象，且「可爱图片」与「表情包梗图」及「双标行为」的内涵完全不符。这不仅是无关，更是对原始问题核心内容的严重稀释和偏离，导致用户目的完全无法达成，属于强负向延伸。\n【最终得分 -0.56】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_双标_r2_q7_9": {
      "type": "sug",
      "query": "[SUG] 双标",
      "level": 23,
      "relevance_score": 0.2,
      "evaluationReason": "【评估对象】词条\"双标\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】sug词条「双标」是原始问题的部分对象，无明确动作意图，无法评估动作匹配度。\n【品类维度 0.25】sug词条《双标》是原始问题中核心限定词之一，体现了部分场景层信息。但缺失原始问题中的核心对象《表情包》《梗图》以及限定词《人类行为》《猫咪》等，覆盖度较低。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“双标”是核心概念，sug词条“双标”是其同义词，不构成延伸。\n【最终得分 0.20】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "q_表情包图片大全_r2_8": {
      "type": "q",
      "query": "[Q] 表情包图片大全",
      "level": 22,
      "relevance_score": 0.17,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_表情包图片大全简笔画_r2_q8_0": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全简笔画",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包图片大全简笔画\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条并没有包含明确的动作意图。因此，sug词条与原始问题在动机上不匹配。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”，限定词是“反映人类双标行为”。Sug词为“表情包图片大全简笔画”，“表情包”部分匹配，但“简笔画”与原始问题的主体“猫咪”和限定词“双标行为梗图”完全不符。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调内容和创意。sug词条「图片大全」和「简笔画」与原始问题的核心目的「制作」和「内容创意」关联度低，反而引入了无关的素材形式和风格，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全微信_r2_q8_1": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全微信",
      "level": 23,
      "relevance_score": -0.12000000000000001,
      "evaluationReason": "【评估对象】词条\"表情包图片大全微信\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 -0.05】原始问题意图是「制作」特定内容的表情包，而Sug词条是「获取/寻找」表情包图片大全。两种意图虽都与表情包相关，但动作方向不同，一个为制作，一个为寻找。\n【品类维度 -0.20】原始问题核心对象为「人类双标行为的猫咪表情包梗图」，场景限定为「反映人类双标行为」。sug词条「表情包图片大全微信」核心对象为「表情包图片」，限定词为「大全」、「微信」。sug词仅泛化匹配到「表情包图片」，但原始问题有更具体的限定，且sug词的限定「微信」与原始问题无关。这种泛化且包含无关限定导致偏离。\n【延伸词维度 -0.15】sug词条「图片大全」和「微信」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关信息，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.12】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全抽象_r2_q8_2": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全抽象",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包图片大全抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」表情包，而sug词条「表情包图片大全抽象」没有明确的动机，无法与原始问题进行动机匹配。\n【品类维度 -0.20】原始问题求《猫咪表情包梗图》，含对象「猫咪表情包」和限定「梗图」。sug词条为《表情包图片大全抽象》，对象为「表情包图片」，限定为「大全」和「抽象」。sug词仅泛化匹配对象「表情包」，但限定词与原始问题不相关、甚至有轻微偏差，缺失核心「猫咪」和「梗图」。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条「图片大全抽象」引入了与制作无关的「大全」和与猫咪表情包主题不符的「抽象」概念，稀释了原始问题的聚焦度。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全可爱_r2_q8_3": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全可爱",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"表情包图片大全可爱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。平台sug词条「表情包图片大全可爱」不包含明确的动作意图。因此，动机维度不匹配，得分为0。\n【品类维度 0.05】sug词条仅包含核心对象“表情包”，但缺失了原始问题中的所有限定词，如“人类双标行为”、“猫咪”、“梗图”。对象匹配度低，且缺失所有场景和具体修饰，导致覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调「人类双标行为」这一核心概念。sug词条「表情包图片大全可爱」中的「图片大全」和「可爱」是延伸词，它们稀释了原始问题中「制作」和「人类双标行为」的特定性与目的性，将需求泛化为普通的表情包浏览，降低了内容的针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全动态_r2_q8_4": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全动态",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包图片大全动态\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”，而sug词条无明确动作意图，只提供了“图片大全”的搜索方向。因此，sug词条与原始问题的制作动机不匹配。\n【品类维度 -0.20】原始问题主体为《人类双标行为的猫咪表情包梗图》，sug词条主体为《表情包图片》。sug词条过度泛化，丢失了核心对象《猫咪》和限定词《人类双标行为》、《梗图》，且仅提及“图片”而忽略了“动态”，存在错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条「图片大全动态」引入了「图片大全」和「动态」这两个延伸词。这两个延伸词与原始问题的「制作」和「梗图」目的关联度低，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全素材_r2_q8_5": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全素材",
      "level": 23,
      "relevance_score": 0.19400000000000003,
      "evaluationReason": "【评估对象】词条\"表情包图片大全素材\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」表情包，sug词条「表情包图片大全素材」无明确动作意图，仅提供素材，与制作动作不匹配。\n【品类维度 0.28】sug词条「表情包图片大全素材」包含了原始问题中的核心对象词「表情包」和「素材」。但缺失了所有的限定词，包括「人类双标行为」、「猫咪」、「梗图」等」等，覆盖度较低，故中低分。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调「人类双标行为」这一创意核心。sug词条「表情包图片大全素材」中的「图片大全素材」是延伸词，它将原始问题从「制作」行为和「双标行为」主题，稀释为泛泛的「素材」获取，降低了内容的针对性和创意性，属于作用域稀释型。\n【最终得分 0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全搞笑_r2_q8_6": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全搞笑",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"表情包图片大全搞笑\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题意图是「制作」反映特定主题的表情包。sug词条「图片大全」没有明确的动作，无法评估动作匹配度。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”的特定制作目的，sug词条“表情包图片大全搞笑”是通用概念，仅包含“表情包图片”，缺失核心主体“猫咪”和“梗图”等限定，且无明确限定词，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调「人类双标行为」这一核心概念。「图片大全搞笑」作为延伸词，与原始问题中的「制作」和「人类双标行为」主题无关，稀释了原始问题的目的性和聚焦度，属于作用域稀释型。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_ch表情包图片大全_r2_q8_7": {
      "type": "sug",
      "query": "[SUG] ch表情包图片大全",
      "level": 23,
      "relevance_score": -0.039999999999999994,
      "evaluationReason": "【评估对象】词条\"ch表情包图片大全\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条「ch表情包图片大全」仅涉及“图片大全”的“获取”或“查看”或“寻找”，无明确制作类动作意图，因此不匹配。\n【品类维度 0.05】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条为「ch表情包图片大全」，对象层为「表情包图片」。sug词条仅在对象层有部分重合，无猫咪、无双标行为等限定，主体过于泛化。\n【延伸词维度 -0.60】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和创作行为。sug词条「ch表情包图片大全」中的「ch」和「图片大全」均为延伸词。「ch」与原始问题无任何关联，属于无关信息。「图片大全」虽然与「表情包」相关，但原始问题是「制作」，而非「获取大全」，且未限定「ch」类型，因此「图片大全」稀释了原始问题的创作目的，并引入了不相关的限定。\n【最终得分 -0.04】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_开心表情包图片大全_r2_q8_8": {
      "type": "sug",
      "query": "[SUG] 开心表情包图片大全",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"开心表情包图片大全\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题是“制作”表情包梗图，而sug词条是“开心表情包图片大全”，sug词条仅提供了表情包本身作为对象，无任何意图动作，无法匹配原始问题的制作意图。\n【品类维度 0.05】原始问题需求是制作『反映人类双标行为的猫咪表情包梗图』，sug词条仅有『开心表情包图片大全』，只覆盖了对象层中的“表情包”，但丢失了“猫咪”、“梗图”、“双标行为”等所有核心限定词，为过度泛化词，故得分较低分值，得分低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条「开心表情包图片大全」引入了「开心」这一情绪限定，且将「制作」目的替换为「图片大全」的浏览需求，稀释了原始问题的核心目的和主题。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_表情包图片大全打印素材_r2_q8_9": {
      "type": "sug",
      "query": "[SUG] 表情包图片大全打印素材",
      "level": 23,
      "relevance_score": -0.23,
      "evaluationReason": "【评估对象】词条\"表情包图片大全打印素材\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题核心动机是「制作」反映双标行为的猫咪表情包梗图，sug词条「表情包图片大全打印素材」无明确的动作意图。\n【品类维度 -0.25】原始问题涉及“猫咪表情包梗图”和“双标行为”语义，sug词为“表情包图片大全打印素材”，主体词“表情包”匹配，但限定词“猫咪”、“双标行为”完全不匹配，反而增加了“图片大全”、“打印”、“素材”等不相关限定，造成核心语义偏离。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条「图片大全」和「打印素材」与原始问题的「制作」和「反映人类双标行为的猫咪表情包梗图」的核心目的关联度低，且「打印素材」引入了与制作无关的新维度，稀释了原始问题的聚焦度。\n【最终得分 -0.23】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "q_梗图meme_r2_9": {
      "type": "q",
      "query": "[Q] 梗图meme",
      "level": 22,
      "relevance_score": 0.17,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_梗图meme双人_r2_q9_0": {
      "type": "sug",
      "query": "[SUG] 梗图meme双人",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"梗图meme双人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”梗图，而sug词条「梗图meme双人」是纯名词短语，无法识别出任何明确的动作意图。因此，sug词条在该维度不具有评估价值。\n【品类维度 0.25】原始问题涉及“猫咪表情包梗图”，sug词条仅包含“梗图”，对象层匹配度低，且缺失所有限定词（人类双标行为、猫咪）。\n【延伸词维度 -0.15】延伸词“meme”是“梗图”的同义词，不构成延伸。延伸词“双人”与原始问题中的“猫咪表情包”和“人类双标行为”无关，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_梗图meme模板_r2_q9_1": {
      "type": "sug",
      "query": "[SUG] 梗图meme模板",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"梗图meme模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」反映特定主题的梗图，sug词条「梗图meme模板」只提及了制作的对象，没有包含任何动作意图，动机完全不匹配。\n【品类维度 0.05】原始问题是关于《人类双标行为的猫咪表情包梗图》制作，包含对象层【梗图】和多个限定词。sug词条仅包含对象层【梗图】的泛化词【梗图meme模板】，缺失所有限定词，且匹配度弱。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一具体内容和主题，而sug词条「梗图meme模板」则过于宽泛，仅提供了制作梗图的通用工具，稀释了原始问题中关于「猫咪表情包」和「人类双标行为」的核心内容，降低了内容的针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_心理疾病meme梗图_r2_q9_2": {
      "type": "sug",
      "query": "[SUG] 心理疾病meme梗图",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"心理疾病meme梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】原始问题的核心动机是「制作」或「生产」一种特定的表情包/梗图，目的是「反映」人类双标行为。\n【动机维度 0.00】原始问题的动机是「制作」或「反映」，而sug词条「心理疾病meme梗图」没有明确的动作意图，仅是名词短语，因此动机维度得分设为0。\n【品类维度 0.05】原始问题核心对象是“人类双标行为”结合“猫咪表情包梗图”，sug词条核心对象是“心理疾病meme梗图”。两者都是梗图，但核心内容主体风马牛不相及，仅“梗图”是共通对象，无法有效匹配。因此给低分。\n【延伸词维度 -0.15】原始问题聚焦于「猫咪表情包梗图」和「人类双标行为」，而sug词条引入了「心理疾病」这一完全不相关的概念，稀释了原始问题的核心主题，属于作用域稀释型。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_梗图meme素材_r2_q9_3": {
      "type": "sug",
      "query": "[SUG] 梗图meme素材",
      "level": 23,
      "relevance_score": 0.37,
      "evaluationReason": "【评估对象】词条\"梗图meme素材\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「梗图meme素材」中不包含明确的动作意图，因此无法进行动作匹配度的评估，动机维度得分为0。\n【品类维度 0.50】原始问题对象层为「人类双标行为的猫咪表情包梗图」，sug词条对象层为「梗图meme素材」。sug词仅覆盖「梗图」且泛化为「素材」，缺失全部限定词，但核心对象匹配度匹配。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，强调创作过程和内容。sug词条「梗图meme素材」将重点从「制作」转移到「素材」，且「meme」与「梗图」重复，稀释了原始问题中「制作」这一核心动机，并引入了原始问题未明确提及的「素材」这一新维度，降低了内容的针对性。\n【最终得分 0.37】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "sug_梗图meme悲伤自嘲_r2_q9_4": {
      "type": "sug",
      "query": "[SUG] 梗图meme悲伤自嘲",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"梗图meme悲伤自嘲\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/反映\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「梗图meme悲伤自嘲」不包含明确的动作意图。\n【品类维度 0.25】原始问题对象层为「表情包梗图」，场景层为「猫咪」和「反映人类双标行为」。sug词条包含「梗图」，但其限定词「悲伤自嘲」与原始问题的限定词相去甚远，且缺失「猫咪」这一核心场景元素。\n【延伸词维度 -0.15】原始问题聚焦于制作「反映人类双标行为的猫咪表情包梗图」，强调了制作方法和具体内容。sug词条「悲伤自嘲」引入了新的情感维度，与原始问题中「双标行为」和「猫咪表情包」的核心内容关联度较低，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_梗图meme代餐_r2_q9_5": {
      "type": "sug",
      "query": "[SUG] 梗图meme代餐",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"梗图meme代餐\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是\"制作\"但sug词条\"梗图meme代餐\"中未包含任何动作意图，因此无法进行动作匹配。\n【品类维度 0.25】原始问题对象层为“猫咪表情包梗图”，场景层为“反映人类双标行为”。Sug词条只有“梗图”，对象层匹配度低，限定词完全缺失，过于宽泛泛匹配。\n【延伸词维度 -0.15】sug词条「meme代餐」与原始问题「猫咪表情包梗图」在概念上存在重叠，但「代餐」一词引入了新的、与原始问题制作梗图目的不符的维度，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_梗图meme学习_r2_q9_6": {
      "type": "sug",
      "query": "[SUG] 梗图meme学习",
      "level": 23,
      "relevance_score": 0.18,
      "evaluationReason": "【评估对象】词条\"梗图meme学习\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.35】原始问题的核心动机是学习「制作」梗图，sug词条的动机是「学习」梗图。制作和学习梗图在动机上是弱相关的，学习可以为制作提供理论基础，但并非直接同义或强相关。\n【品类维度 0.05】原始问题核心对象是「反映人类双标行为的猫咪表情包梗图」，sug词条仅包含通用词「梗图」，缺失核心对象「猫咪表情包」及限定词。匹配度很低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的「猫咪表情包梗图」，而sug词条的「meme学习」虽然与「梗图」相关，但「学习」这一动机与原始问题的「制作」存在偏差，且「meme」是「梗图」的同义词，未引入新的有益信息，反而稀释了原始问题中「猫咪表情包」和「双标行为」的特定主题，导致聚焦度下降。\n【最终得分 0.18】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_焦虑症meme梗图_r2_q9_7": {
      "type": "sug",
      "query": "[SUG] 焦虑症meme梗图",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"焦虑症meme梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图。Sug词条「焦虑症meme梗图」无明确动作意图，因此动机匹配度为0。\n【品类维度 -0.20】原始问题核心对象是《猫咪表情包梗图》和《人类双标行为》，sug词是《焦虑症meme梗图》。sug词的主体《焦虑症》与原始问题主体《猫咪》和《人类双标行为》基本无关联，品类冲突。\n【延伸词维度 -0.15】sug词条「焦虑症」和「meme」与原始问题中的「人类双标行为」和「猫咪表情包梗图」无直接关联，引入了不相关的概念，稀释了原始问题的聚焦度。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_精神疾病meme梗图_r2_q9_8": {
      "type": "sug",
      "query": "[SUG] 精神疾病meme梗图",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"精神疾病meme梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是【制作】表情包梗图，sug词条无法识别明确的动作意图。虽然都与meme梗图有关，但动机维度上sug词条未覆盖原始问题的动作需求，因此动机维度评分为0。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词条核心对象为「梗图」，限定词为「精神疾病meme」。二者对象虽然都包含「梗图」，但其核心限定词「猫咪表情包」和「精神疾病meme」完全不同，且有误导性。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的制作，而sug词条「精神疾病meme梗图」引入了与原始问题主题无关的「精神疾病」概念，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.17
    },
    "sug_梗图meme原创_r2_q9_9": {
      "type": "sug",
      "query": "[SUG] 梗图meme原创",
      "level": 23,
      "relevance_score": 0.654,
      "evaluationReason": "【评估对象】词条\"梗图meme原创\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.90】原始问题核心动机是“制作”一份特殊的“表情包/梗图”，sug词条「梗图meme原创」也包含“原创/制作”和“梗图”，因此动机高度匹配。\n【品类维度 0.08】原始问题涉及“猫咪表情包梗图”的制作，主体是“猫咪表情包梗图”及“人类双标行为”这一限定。sug词条“梗图meme原创”仅包含宽泛的主体“梗图”，缺失了“猫咪表情包”及“人类双标行为”等所有限定词，匹配度低。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“梗图”与sug词条中的“梗图meme”是同义词，不构成延伸。\n【最终得分 0.65】\n【规则说明】情况4：无延伸词，权重调整为 动机70% + 品类30%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.17
    },
    "q_梗图分享_r2_10": {
      "type": "q",
      "query": "[Q] 梗图分享",
      "level": 22,
      "relevance_score": 0.085,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": ""
    },
    "sug_恋与深空同人图资源分享_r2_q10_0": {
      "type": "sug",
      "query": "[SUG] 恋与深空同人图资源分享",
      "level": 23,
      "relevance_score": -0.36000000000000004,
      "evaluationReason": "【评估对象】词条\"恋与深空同人图资源分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 -0.20】原始问题的核心动机是\"制作\"表情包梗图，而sug词条的动机是\"分享\"资源，两者动作方向不同，但都涉及创作或内容流转，因此得分-0.2。\n【品类维度 -0.50】原始问题是关于《猫咪表情包》制作，sug词是《恋与深空同人图》。两者核心对象和限定词完全不匹配，品类完全冲突，主题完全不同，负相关。\n【延伸词维度 -0.60】原始问题是关于「制作反映人类双标行为的猫咪表情包梗图」，核心是「制作」、「猫咪表情包」、「双标行为」。sug词条「恋与深空同人图资源分享」中的「恋与深空」、「同人图」、「资源分享」均与原始问题的作用域完全不符，引入了全新的、不相关的概念，严重稀释了原始问题的聚焦度，且无任何辅助作用，属于强负向延伸。\n【最终得分 -0.36】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_早安分享图片_r2_q10_1": {
      "type": "sug",
      "query": "[SUG] 早安分享图片",
      "level": 23,
      "relevance_score": -0.21500000000000002,
      "evaluationReason": "【评估对象】词条\"早安分享图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」，而sug词条「早安分享图片」的核心动机是「分享」。两者动作意图完全不匹配，且sug词条未包含原始问题制作表情包的任何意图。\n【品类维度 -0.50】原始问题主要对象是“猫咪表情包梗图”和“人类双标行为”，场景限定是“制作”。sug词条是“早安分享图片”，两者对象和场景均不匹配，品类显著错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定创意内容，而sug词条「早安分享图片」则是一个宽泛且与原始问题核心内容无关的日常分享行为。该延伸词引入了与原始问题完全不相关的概念，稀释了原始问题的聚焦度，降低了内容针对性，使其偏离了核心目的。\n【最终得分 -0.22】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_定制分享图_r2_q10_2": {
      "type": "sug",
      "query": "[SUG] 定制分享图",
      "level": 23,
      "relevance_score": 0.07999999999999997,
      "evaluationReason": "【评估对象】词条\"定制分享图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.35】原始问题的核心动机是“制作”表情包梗图，而sug词条是“定制”分享图。“制作”与“定制”虽然都含“创作”之意，但“定制”更侧重个性化或特定需求，与“制作”属弱相关，方向上有一定程度的偏差。\n【品类维度 -0.20】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条「定制分享图」与核心对象及限定词均不匹配，品类错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映人类双标行为的「猫咪表情包梗图」这一具体内容创作过程。「定制分享图」中的「定制」与「制作」有部分重叠，但「分享图」是结果而非制作过程，且未提及「猫咪表情包梗图」这一核心对象。延伸词「分享图」将重点从「制作」转移到「分享」，且未包含原始问题的核心对象，稀释了原始问题的聚焦度。\n【最终得分 0.08】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_图纸分享_r2_q10_3": {
      "type": "sug",
      "query": "[SUG] 图纸分享",
      "level": 23,
      "relevance_score": -0.35500000000000004,
      "evaluationReason": "【评估对象】词条\"图纸分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「图纸分享」的核心动机是「分享」。两个动作不相关。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」；Sug词条对象层为「图纸」。两者核心主体完全不匹配，品类冲突严重，方向完全错误。\n【延伸词维度 -0.15】原始问题是关于「制作」表情包梗图，而sug词条「图纸分享」引入了与制作无关的「分享」行为，且「图纸」与「表情包梗图」概念不符，稀释了原始问题的聚焦度。\n【最终得分 -0.36】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_meme梗图分享_r2_q10_4": {
      "type": "sug",
      "query": "[SUG] meme梗图分享",
      "level": 23,
      "relevance_score": 0.21000000000000002,
      "evaluationReason": "【评估对象】词条\"meme梗图分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.25】原始问题的核心动机是「制作」meme梗图。sug词条「meme梗图分享」的动机是「分享」。分享是制作后的相关步骤，但并非核心动机，属于弱相关。\n【品类维度 0.25】原始问题对象层为“猫咪表情包梗图”，场景层为“反映人类双标行为”；sug词只包含“meme梗图”，属于对象层的泛化，场景层完全缺失。sug词过度泛化。\n【延伸词维度 -0.15】原始问题聚焦于「制作」特定主题的表情包梗图，而sug词条「分享」则引入了新的行为维度，且未提及猫咪和双标行为，稀释了原始问题的核心目的和主题。\n【最终得分 0.21】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.085
    },
    "sug_拼豆豆图纸分享_r2_q10_5": {
      "type": "sug",
      "query": "[SUG] 拼豆豆图纸分享",
      "level": 23,
      "relevance_score": -0.75,
      "evaluationReason": "【评估对象】词条\"拼豆豆图纸分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成\n【动机维度 -0.70】原始问题的核心动机是「制作反映人类双标行为的猫咪表情包梗图」，sug词条的动机是「分享」拼豆豆图纸，两者动作意图完全不相关，且制作与分享方向相反。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条对象层为「拼豆豆图纸」，两者在对象层完全不匹配，品类冲突严重，无任何关联。\n【延伸词维度 -0.60】原始问题聚焦于「猫咪表情包梗图」的「制作」和「反映人类双标行为」这一主题。sug词条「拼豆豆图纸分享」引入了完全不相关的「拼豆豆」这一制作形式和「图纸分享」这一行为，与原始问题的核心对象、动机和主题均不符，属于典型的作用域稀释型延伸词，且稀释程度高。\n【最终得分 -0.75】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_买断图分享_r2_q10_6": {
      "type": "sug",
      "query": "[SUG] 买断图分享",
      "level": 23,
      "relevance_score": -0.5650000000000001,
      "evaluationReason": "【评估对象】词条\"买断图分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/形成\n【动机维度 -0.70】原始问题核心动机是「制作」或「形成」，而sug词条「买断图分享」的核心动机是「买断」（购买）与「分享」。两者动作意图完全相反。\n【品类维度 -0.50】原始问题是关于“猫咪表情包梗图”的制作，以及其主题“人类双标行为”，对象层为“猫咪表情包梗图”。Sug词为“买断图分享”，仅提及“图”且无任何限定词，与原始问题的核心对象和特定主题均不匹配，存在品类错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，而sug词条「买断图分享」引入了与制作无关的「买断」和「分享」概念，稀释了原始问题的核心目的，属于作用域稀释型。\n【最终得分 -0.57】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_拼豆图纸分享_r2_q10_7": {
      "type": "sug",
      "query": "[SUG] 拼豆图纸分享",
      "level": 23,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"拼豆图纸分享\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「拼豆图纸分享」的核心动机是「分享」图纸，两者动作意图完全不匹配。\n【品类维度 -0.80】原始问题是关于《猫咪表情包梗图》制作，涉及对象层《梗图》和场景层《猫咪》、《双标行为》。Sug词是《拼豆图纸分享》，对象层为《图纸》，与原始问题对象《梗图》品类完全不符，无任何关联性。\n【延伸词维度 -0.60】sug词条「拼豆图纸分享」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题、内容和目的上完全不相关，引入了与原始问题无关的全新概念，严重稀释了原始问题的聚焦度，导致内容完全偏离，属于作用域稀释型。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_日常分享图片_r2_q10_8": {
      "type": "sug",
      "query": "[SUG] 日常分享图片",
      "level": 23,
      "relevance_score": -0.12000000000000001,
      "evaluationReason": "【评估对象】词条\"日常分享图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 -0.05】原始问题意图是「制作」特定内容的表情包梗图。sug词条「日常分享图片」的意图是「分享」图片，虽然都涉及图片，但原始问题是重在创作和产出，sug词条重在传播，两者方向存在偏移。因此，评分为-0.05。\n【品类维度 -0.20】原始问题需「猫咪表情包梗图」，涉及特定内容、主题和形式。sug词「日常分享图片」泛化度过高，无法体现特定创作对象或主题，存在明显错位，故得分较低。\n【延伸词维度 -0.15】sug词条「日常分享图片」中的「日常分享」和「图片」均与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和具体对象不符，引入了无关信息，稀释了原始问题的聚焦度，属于作用域稀释型延伸词。\n【最终得分 -0.12】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "sug_自截分享图_r2_q10_9": {
      "type": "sug",
      "query": "[SUG] 自截分享图",
      "level": 23,
      "relevance_score": -0.015,
      "evaluationReason": "【评估对象】词条\"自截分享图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题主要动机是《制作》梗图，而sug词条《自截分享图》中《自截》与《制作》有部分关联，但《分享》部分和原始问题不匹配，且无法完全替代原始问题的动机。\n【品类维度 0.00】原始问题主要对象是“猫咪表情包梗图”，限定词是“人类双标行为”；sug词是“自截分享图”。二者内容主体差异极大，无关联性。\n【延伸词维度 -0.15】原始问题是关于「制作」特定主题的表情包梗图，而sug词条「自截分享图」与制作行为无关，且未提及猫咪或双标行为，稀释了原始问题的核心目的和主题。\n【最终得分 -0.01】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.085
    },
    "q_猫咪表情包梗图_r2_11": {
      "type": "q",
      "query": "[Q] 猫咪表情包梗图",
      "level": 22,
      "relevance_score": 0.23399999999999999,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D3"
    },
    "sug_猫咪表情包_r2_q11_0": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包",
      "level": 23,
      "relevance_score": 0.48,
      "evaluationReason": "【评估对象】词条\"猫咪表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包和梗图，而sug词条「猫咪表情包」是一个名词，没有明确的动作意图，因此无法评估动作匹配度。\n【品类维度 0.60】sug词条「猫咪表情包」与原始问题在对象层「猫咪表情包」完全匹配。虽然sug词条未涵盖原始问题中所有限定词（如「人类双标行为」、「梗图」），导致覆盖度非100%，但核心对象一致。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。\n【最终得分 0.48】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.23399999999999999
    },
    "sug_猫咪表情包图片_r2_q11_1": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包图片",
      "level": 23,
      "relevance_score": 0.52,
      "evaluationReason": "【评估对象】词条\"猫咪表情包图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条「猫咪表情包图片」仅为一个对象描述，没有体现任何动作意图。sug词条缺失动机层，故动机维度匹配度为0。\n【品类维度 0.65】原始问题对象层为“猫咪表情包梗图”，限定词有“人类双标行为”；Sug词仅包含“猫咪表情包图片”，对象匹配但在场景限定上缺失“人类双标行为”和“梗图”更具体的限定，覆盖度适中。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题核心是“猫咪表情包”，sug词条中的“猫咪表情包”是核心对象，而“图片”是其表现形式，属于细化，不构成延伸。\n【最终得分 0.52】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.23399999999999999
    },
    "sug_猫咪咪表情包图片_r2_q11_2": {
      "type": "sug",
      "query": "[SUG] 猫咪咪表情包图片",
      "level": 23,
      "relevance_score": 0.41000000000000003,
      "evaluationReason": "【评估对象】词条\"猫咪咪表情包图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】「制作」猫咪表情包梗图，反映人类双标行为\n【动机维度 0.00】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「猫咪咪表情包图片」没有明确的动作意图。\n【品类维度 0.55】原始问题对象层为“猫咪表情包梗图”，限定词为“反映人类双标行为”；sug词对象层为“猫咪咪表情包图片”，未包含任何限定词。对象层匹配，但sug词未包含限定词，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映「人类双标行为」的「猫咪表情包梗图」，强调制作方法和特定主题。sug词条「猫咪咪表情包图片」将「制作」和「人类双标行为」这两个核心动机和限定条件稀释，仅保留了「猫咪表情包」这一对象，且将「梗图」替换为更宽泛的「图片」，降低了内容的针对性和深度，属于作用域稀释型。\n【最终得分 0.41】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.23399999999999999
    },
    "sug_猫咪搞笑表情包_r2_q11_3": {
      "type": "sug",
      "query": "[SUG] 猫咪搞笑表情包",
      "level": 23,
      "relevance_score": 0.44999999999999996,
      "evaluationReason": "【评估对象】词条\"猫咪搞笑表情包\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「猫咪搞笑表情包」并没有体现任何动作意图，因此动机匹配度为0。\n【品类维度 0.60】原始问题对象层为「人类双标行为的猫咪表情包梗图」，场景层无。sug词条对象层为「猫咪搞笑表情包」，场景层无。sug词条的主体词「猫咪表情包」与原始问题主体词「猫咪表情包」匹配，但sug词「搞笑」无法涵盖原始问题「人类双标行为」这一限定。覆盖度计算：1/2=50%。\n【延伸词维度 -0.15】原始问题聚焦于“反映人类双标行为”这一特定主题的猫咪表情包梗图制作。sug词条“搞笑”虽然是表情包的常见属性，但它稀释了原始问题中“双标行为”这一核心概念的聚焦度，使其偏离了原始问题的特定目的，属于作用域稀释型。\n【最终得分 0.45】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.23399999999999999
    },
    "sug_猫咪表情包梗图搞笑_r2_q11_4": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包梗图搞笑",
      "level": 23,
      "relevance_score": 0.6000000000000001,
      "evaluationReason": "【评估对象】词条\"猫咪表情包梗图搞笑\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条「猫咪表情包梗图搞笑」并未包含明确的动作意图，仅是对内容或主题的描述，因此无法评估动作匹配度。\n【品类维度 0.75】原始问题对象层为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词条「猫咪表情包梗图搞笑」包含了原始问题的完整对象层「猫咪表情包梗图」，但在限定词上，sug词条的「搞笑」是新的限定词，原始问题则无此限定，覆盖度适中故给0.75分。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。\n【最终得分 0.60】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.23399999999999999
    },
    "q_猫咪表情包_r2_12": {
      "type": "q",
      "query": "[Q] 猫咪表情包",
      "level": 22,
      "relevance_score": 0.21059999999999998,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D3"
    },
    "sug_猫咪表情包抽象_r2_q12_0": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包抽象",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"猫咪表情包抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】sug词条「猫咪表情包抽象」未体现出明确的动作意图和目的，主要描述的是内容主题，因此在动机维度上无法匹配原始问题的「制作」意图。\n【品类维度 0.08】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条包含「猫咪表情包」，但缺失「梗图」和所有场景层限定，覆盖度低且过度泛化。\n【延伸词维度 -0.15】原始问题聚焦于「双标行为」这一特定主题的表情包制作，而sug词条「抽象」引入了新的、更宽泛的风格维度，稀释了原始问题的核心主题，降低了内容的针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫meme表情包动图_r2_q12_1": {
      "type": "sug",
      "query": "[SUG] 猫meme表情包动图",
      "level": 23,
      "relevance_score": 0.36,
      "evaluationReason": "【评估对象】词条\"猫meme表情包动图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「猫meme表情包动图」核心动机是「查找」或「浏览」猫咪相关的表情包动图，与「制作」存在一定程度的间接关联。\n【品类维度 0.50】原始问题核心对象层为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词条「猫meme表情包动图」涵盖了核心对象「猫咪表情包」及部分限定词（meme≈梗图），但缺失「双标行为」这一关键限定，且新增「动图」限定。整体匹配度中等。\n【延伸词维度 -0.15】原始问题聚焦于“人类双标行为”这一特定主题的猫咪表情包梗图制作，强调内容创意。sug词条“猫meme表情包动图”将“梗图”具体化为“动图”，并引入了“meme”这一更宽泛的概念，稀释了原始问题中“人类双标行为”这一核心主题的聚焦度，降低了内容的针对性。\n【最终得分 0.36】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包配文_r2_q12_2": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包配文",
      "level": 23,
      "relevance_score": 0.38,
      "evaluationReason": "【评估对象】词条\"猫咪表情包配文\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.35】原始问题的核心动作为“制作”，sug词条“配文”是制作表情包过程中所需要的其中一个步骤，属于弱相关\n【品类维度 0.55】原始问题对象层为「猫咪表情包梗图」，限定词为「反映人类双标行为」。Sug词条对象层为「猫咪表情包配文」。对象主体「猫咪表情包」匹配，限定词缺失，但「配文」是「梗图」的重要组成部分。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「梗图」的制作，而sug词条「配文」虽然是表情包的一部分，但它将原始问题中「双标行为」和「梗图」的核心概念稀释，使其偏离了原始问题的核心目的，降低了内容的针对性。\n【最终得分 0.38】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包动图_r2_q12_3": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包动图",
      "level": 23,
      "relevance_score": 0.41000000000000003,
      "evaluationReason": "【评估对象】词条\"猫咪表情包动图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题核心动作用于《制作》表情包梗图，sug词条仅提及《表情包》这一对象而无任何动作意图，因此动机匹配度为0。\n【品类维度 0.55】原始问题对象层为“猫咪表情包梗图”，限定词为“反映人类双标行为”；sug词对象层为“猫咪表情包动图”。对象层“猫咪表情包”核心主体匹配，但限定词“梗图”与“动图”不完全一致，且缺失原始问题所有限定词，故中等偏上评分。\n【延伸词维度 -0.15】原始问题聚焦于「反映人类双标行为」的特定主题，而sug词条「动图」引入了无关的格式限定，稀释了主题的聚焦度，降低了内容针对性。\n【最终得分 0.41】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包制作_r2_q12_4": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包制作",
      "level": 23,
      "relevance_score": 0.825,
      "evaluationReason": "【评估对象】词条\"猫咪表情包制作\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.90】原始问题的核心动机是「制作」表情包梗图，sug词条「猫咪表情包制作」也包含了「制作」的动作，且对象是「表情包」，动作完全匹配。\n【品类维度 0.65】原始问题对象层为“猫咪表情包梗图”，场景层为“反映人类双标行为”；Sug词条对象层为“猫咪表情包”。Sug词条包含了核心对象“猫咪表情包”，但缺失了重要的场景限定“反映人类双标行为”，覆盖度约为50%，属于部分匹配。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。sug词条是原始问题的简化，未增加新的信息维度。\n【最终得分 0.82】\n【规则说明】情况4：无延伸词，权重调整为 动机70% + 品类30%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包可爱_r2_q12_5": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包可爱",
      "level": 23,
      "relevance_score": 0.37,
      "evaluationReason": "【评估对象】词条\"猫咪表情包可爱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「猫咪表情包可爱」没有明确的动作意图，因此无法匹配，得分为0。\n【品类维度 0.50】核心对象层为“猫咪表情包”，sug词条完全命中。原始问题的特有对象层修饰词“反映人类双标行为的”以及场景层“梗图”未命中，覆盖度50%。\n【延伸词维度 -0.15】原始问题聚焦于「反映人类双标行为」的「梗图」制作，强调主题性和创作性。「可爱」作为延伸词，虽然是猫咪表情包的常见属性，但与原始问题中「双标行为」和「梗图」的核心目的关联度低，且可能稀释了原始问题对特定主题和创作手法的聚焦，属于作用域稀释型。\n【最终得分 0.37】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情符号_r2_q12_6": {
      "type": "sug",
      "query": "[SUG] 猫咪表情符号",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"猫咪表情符号\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是“制作”表情包梗图，而sug词条「猫咪表情符号」只提及了一个对象和主题，没有明确的动作意图，无法匹配原始问题的制作动机。\n【品类维度 0.25】原始问题涉及“猫咪+表情包+梗图”以及“人类双标行为”的特定场景，sug词条仅包含“猫咪+表情符号”，对象层部分匹配。场景和具体概念严重缺失，覆盖度很低。虽有“猫咪”和“表情”关联，但深度和广度不足。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，强调了制作行为、双标主题和梗图形式。「表情符号」作为延伸词，与「表情包梗图」存在差异，稀释了原始问题对「梗图」和「双标行为」的特定需求，降低了内容的针对性。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包叫什么_r2_q12_7": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包叫什么",
      "level": 23,
      "relevance_score": 0.185,
      "evaluationReason": "【评估对象】词条\"猫咪表情包叫什么\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动是「制作」表情包，而sug词条「猫咪表情包叫什么」是一个提问，意图是「获取名称信息」。sug词条无明确动机词，与原始问题的制作意图无关。\n【品类维度 0.50】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。sug词条对象层为「猫咪表情包」，与原始问题核心主体匹配，但缺失关键场景限定词及「梗图」限定。\n【延伸词维度 -0.15】sug词条「叫什么」引入了对猫咪表情包名称的询问，这与原始问题中「制作」表情包的动机和「反映人类双标行为」的对象完全不符，稀释了原始问题的核心目的和聚焦度。\n【最终得分 0.18】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包图片_r2_q12_8": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包图片",
      "level": 23,
      "relevance_score": 0.52,
      "evaluationReason": "【评估对象】词条\"猫咪表情包图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条「猫咪表情包图片」仅为一个对象描述，没有体现任何动作意图。sug词条缺失动机层，故动机维度匹配度为0。\n【品类维度 0.65】原始问题对象层为“猫咪表情包梗图”，限定词有“人类双标行为”；Sug词仅包含“猫咪表情包图片”，对象匹配但在场景限定上缺失“人类双标行为”和“梗图”更具体的限定，覆盖度适中。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题核心是“猫咪表情包”，sug词条中的“猫咪表情包”是核心对象，而“图片”是其表现形式，属于细化，不构成延伸。\n【最终得分 0.52】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪表情包视频_r2_q12_9": {
      "type": "sug",
      "query": "[SUG] 猫咪表情包视频",
      "level": 23,
      "relevance_score": 0.455,
      "evaluationReason": "【评估对象】词条\"猫咪表情包视频\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.50】原始问题的核心动机是\"制作\"表情包梗图，而sug词条「猫咪表情包视频」的动作是制作「视频」。虽然都是「制作」大类，但对象由静态的「表情包梗图」变成了动态的「视频」，属于相关动作，但不完全匹配。\n【品类维度 0.55】原始问题对象层为「猫咪表情包梗图」，场景层为「双标行为」。sug词条对象层为「猫咪表情包视频」。对象层核心词“猫咪表情包”匹配，但限定词“梗图”与“视频”不完全匹配，且缺失「双标行为」限定。\n【延伸词维度 -0.15】原始问题是制作“表情包梗图”，强调静态图片和梗的创作。sug词条引入“视频”这一延伸词，改变了原始问题的媒介形式，稀释了对“梗图”制作的聚焦，属于作用域稀释型。\n【最终得分 0.46】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "q_猫咪梗图_r2_13": {
      "type": "q",
      "query": "[Q] 猫咪梗图",
      "level": 22,
      "relevance_score": 0.21059999999999998,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D3"
    },
    "sug_猫咪梗图素材_r2_q13_0": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图素材",
      "level": 23,
      "relevance_score": 0.4,
      "evaluationReason": "【评估对象】词条\"猫咪梗图素材\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪梗图，sug词条是「猫咪梗图素材」，sug词条没有明确的动机意图，无法评估动作匹配度。\n【品类维度 0.50】原始问题对象层为“猫咪表情包梗图”，限定词为“人类双标行为”，sug词条仅包含核心对象“猫咪梗图（素材）”，限定词缺失。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“表情包梗图”与sug词条中的“梗图”是同义词，而“素材”是制作梗图的必要组成部分，属于原始问题作用域内的词汇。\n【最终得分 0.40】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图模板_r2_q13_1": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图模板",
      "level": 23,
      "relevance_score": 0.4,
      "evaluationReason": "【评估对象】词条\"猫咪梗图模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（动）+ 表情包梗图（对象）+ 反映人类双标行为的猫咪（场景/目的）\n【动机维度 0.00】原始问题的核心动机是“制作”，而sug词条“猫咪梗图模板”中缺失明确的动作意图。\n【品类维度 0.50】原始问题对象层为「人类双标行为的猫咪表情包梗图」，sug词条对象层为「猫咪梗图模板」，仅包含核心对象「猫咪梗图」，但场景层和具体限定词缺失。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题是制作“猫咪表情包梗图”，sug词条是“猫咪梗图模板”，模板是制作梗图的工具，属于原始问题对象层，因此不构成延伸词。\n【最终得分 0.40】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图骂人_r2_q13_2": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图骂人",
      "level": 23,
      "relevance_score": 0.34500000000000003,
      "evaluationReason": "【评估对象】词条\"猫咪梗图骂人\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.40】原始问题的核心动机是「制作」反映特定主题的表情包梗图。sug词条「猫咪梗图骂人」的动机是「制作」或「寻找」猫咪梗图，方向上与原始问题中的「制作」表情包梗图是弱相关的实现路径。\n【品类维度 0.40】sug词条与原始问题都包含核心对象“猫咪梗图”，但sug词条的限定词“骂人”与原始问题的“人类双标行为”语义不匹配，且缺失『表情包』限定，覆盖度较低。\n【延伸词维度 -0.15】原始问题聚焦于制作反映人类双标行为的猫咪表情包梗图，强调「双标行为」这一特定主题。sug词条「骂人」引入了新的、更宽泛且可能负面的情绪表达，稀释了原始问题中「双标行为」这一核心概念的聚焦度，降低了内容的针对性。\n【最终得分 0.35】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图恋爱_r2_q13_3": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图恋爱",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"猫咪梗图恋爱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」反映特定主题的猫咪梗图。sug词条「猫咪梗图恋爱」缺失了明确的动机词，无法与「制作」动作匹配，因此动机维度评分为0。\n【品类维度 -0.20】原始问题是关于“人类双标行为”的“猫咪表情包梗图”。Sug词是“猫咪梗图恋爱”。两者核心主体都是“猫咪梗图”，匹配。但原始问题限定词是“人类双标行为”，sug词的限定词是“恋爱”，两者完全不相关且语义偏离，导向错误。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」这一主题的猫咪表情包梗图制作，而sug词条引入了「恋爱」这一新的主题，稀释了原始问题的核心聚焦，使其偏离了「双标行为」的特定内容，降低了内容的针对性。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图伤感_r2_q13_4": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图伤感",
      "level": 23,
      "relevance_score": 0.33000000000000007,
      "evaluationReason": "【评估对象】词条\"猫咪梗图伤感\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】sug词条「猫咪梗图伤感」只有对象（猫咪梗图）和情绪（伤感），没有明确的动作意图，无法与原始问题中的“制作”动作进行匹配。\n【品类维度 0.45】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「猫咪梗图」，场景层为「伤感」。核心对象「猫咪梗图」匹配，但场景层差异较大，原始问题限定词「反映人类双标」未覆盖，Sug词引入新限定词「伤感」。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」这一特定主题的猫咪梗图制作，而sug词条「伤感」引入了新的情感维度，与原始问题的核心主题不符，稀释了原始问题的聚焦度。\n【最终得分 0.33】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图睡觉_r2_q13_5": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图睡觉",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"猫咪梗图睡觉\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题是「制作」反映双标行为的猫咪表情包梗图，核心动作为制作。Sug词条「猫咪梗图睡觉」无明确动作意图，动机维度不匹配。\n【品类维度 0.25】原始问题对象层为“猫咪表情包梗图”，限定词是“反映人类双标行为”；sug词条对象层为“猫咪梗图”，限定词是“睡觉”。二者对象层部分匹配（猫咪梗图），但限定词完全不匹配，语义错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」，强调「双标行为」和「表情包」的创作。sug词条「睡觉」引入了与原始问题核心目的无关的新主题，稀释了对「双标行为」和「表情包制作」的聚焦，属于作用域稀释型。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图英文_r2_q13_6": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图英文",
      "level": 23,
      "relevance_score": 0.29000000000000004,
      "evaluationReason": "【评估对象】词条\"猫咪梗图英文\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「猫咪梗图英文」只提到了主题和格式（英文），没有体现任何动作意图，因此动机匹配度为零。\n【品类维度 0.40】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条对象层为「猫咪梗图」，与原始问题核心主体匹配。但sug词条的限定词「英文」与原始问题限定词「人类双标行为」完全不匹配，且「表情包」这一重要限定词也缺失。\n【延伸词维度 -0.15】延伸词“英文”与原始问题“制作反映人类双标行为的猫咪表情包梗图”的核心目的和作用域无关，稀释了用户对制作方法和内容的关注度，属于作用域稀释型。\n【最终得分 0.29】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图塔牌_r2_q13_7": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图塔牌",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"猫咪梗图塔牌\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」反映人类双标行为的猫咪表情包梗图。sug词条「猫咪梗图塔牌」无法识别明确的动作意图。因此动机维度得分设为0。\n【品类维度 0.05】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条包含「猫咪梗图」，匹配部分对象层，但缺失所有限定词。\n【延伸词维度 -0.15】sug词条中的“塔牌”与原始问题“如何制作反映人类双标行为的猫咪表情包梗图”的核心目的和作用域无关，引入了无关信息，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图拍照_r2_q13_8": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图拍照",
      "level": 23,
      "relevance_score": 0.29999999999999993,
      "evaluationReason": "【评估对象】词条\"猫咪梗图拍照\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.35】原始问题意图是「制作」反映特定行为的「猫咪表情包梗图」。sug词条「猫咪梗图拍照」的动作是「拍照」，这是制作梗图的一个前置或相关动作，但并非核心「制作」意图，属于弱相关。\n【品类维度 0.35】原始问题对象层为《人类双标行为的猫咪表情包梗图》，作用域限定词为《人类双标行为》。sug词条对象层为《猫咪梗图》，限定词缺失且未提及《表情包》和《人类双标行为》。\n【延伸词维度 -0.15】原始问题聚焦于「制作」反映双标行为的「猫咪表情包梗图」，强调内容创作和主题。sug词条「拍照」引入了新的动作，且「拍照」与「制作」表情包梗图并非完全等同，稀释了原始问题中「制作」和「双标行为」的核心目的，降低了内容针对性。\n【最终得分 0.30】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.21059999999999998
    },
    "sug_猫咪梗图上帝_r2_q13_9": {
      "type": "sug",
      "query": "[SUG] 猫咪梗图上帝",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"猫咪梗图上帝\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题明确意图是“制作”梗图，而sug词条「猫咪梗图上帝」是一个名词，没有明确的动作意图。因此，sug词条无法提供制作的相关动作，导致动机维度得分低。\n【品类维度 0.25】原始问题问的是“梗图”，sug词条只出现“梗图”，对象层匹配。但原始问题强调“人类双标行为”和“猫咪”这两个重要限定词，sug词条未提及，且“上帝”属于过度泛化和抽象词汇，覆盖度较低。\n【延伸词维度 -0.15】sug词条「上帝」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域无关，引入了无关信息，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.21059999999999998
    },
    "q_表情包梗图_r2_14": {
      "type": "q",
      "query": "[Q] 表情包梗图",
      "level": 22,
      "relevance_score": 0.1755,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D3"
    },
    "sug_表情包梗图模板_r2_q14_0": {
      "type": "sug",
      "query": "[SUG] 表情包梗图模板",
      "level": 23,
      "relevance_score": 0.19400000000000003,
      "evaluationReason": "【评估对象】词条\"表情包梗图模板\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图，而sug词条「表情包梗图模板」中不包含明确的动作意图。因此，sug词条无法识别动作意图，动机维度得分0分。\n【品类维度 0.28】sug词条仅包含原始问题中最宽泛的“表情包梗图”这一核心对象，缺失『人类双标行为』、『猫咪』等重要的限定词，覆盖度低。\n【延伸词维度 -0.15】原始问题聚焦于「制作反映人类双标行为的猫咪表情包梗图」这一特定主题和内容，而sug词条「模板」则将范围泛化，稀释了原始问题的核心内容和目的，属于作用域稀释型。\n【最终得分 0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图抽象_r2_q14_1": {
      "type": "sug",
      "query": "[SUG] 表情包梗图抽象",
      "level": 23,
      "relevance_score": 0.37,
      "evaluationReason": "【评估对象】词条\"表情包梗图抽象\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是「制作」，而sug词条「表情包梗图抽象」中没有明确的动作意图。\n【品类维度 0.50】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「表情包梗图」。对象层命中「表情包梗图」，但其是猫咪表情包梗图的泛化，且缺失所有场景限定词，属于部分匹配。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的结合，强调具体内容和形式。「抽象」作为延伸词，与原始问题中的具体内容和形式无关，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.37】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.1755
    },
    "sug_jojo表情包梗图_r2_q14_2": {
      "type": "sug",
      "query": "[SUG] jojo表情包梗图",
      "level": 23,
      "relevance_score": -0.3500000000000001,
      "evaluationReason": "【评估对象】词条\"jojo表情包梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。平台sug词条「jojo表情包梗图」没有明确的动作意图。因此，动机维度得分为0。\n【品类维度 -0.40】原始问题核心对象是「猫咪」「表情包」「梗图」，sug词条只匹配「表情包」和「梗图」，但核心主题「猫咪」被替换为「jojo」，存在主题错位，导致关联度降低。\n【延伸词维度 -0.15】sug词条中的“jojo”是延伸词，它引入了与原始问题“猫咪表情包”完全不相关的动漫主题，稀释了原始问题对“猫咪”和“双标行为”的聚焦，降低了内容的针对性。\n【最终得分 -0.35】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图学习_r2_q14_3": {
      "type": "sug",
      "query": "[SUG] 表情包梗图学习",
      "level": 23,
      "relevance_score": 0.39499999999999996,
      "evaluationReason": "【评估对象】词条\"表情包梗图学习\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.35】原始问题意图是「制作」，sug词条意图是「学习」。学习是制作的前置相关路径或准备，属于弱相关。\n【品类维度 0.50】原始问题对象层为“猫咪表情包梗图”，限定词有“反映人类双标行为”；sug词条对象层为“表情包梗图”，缺失限定词，核心主体匹配，但限定词缺失。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。\n【最终得分 0.39】\n【规则说明】情况4：无延伸词，权重调整为 动机70% + 品类30%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图动图_r2_q14_4": {
      "type": "sug",
      "query": "[SUG] 表情包梗图动图",
      "level": 23,
      "relevance_score": 0.41000000000000003,
      "evaluationReason": "【评估对象】词条\"表情包梗图动图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题核心动机是“制作表情包”，而sug词条「表情包梗图动图」是一个纯名词短语，无法识别出任何动作意图，因此无法评估动作的匹配度。\n【品类维度 0.50】原始问题核心对象是“猫咪表情包梗图”，sug词为“表情包梗图动图”。sug词包含核心对象，但缺失“猫咪”和“双标行为”的限定，且多了一个“动图”的无关限定。\n【延伸词维度 0.05】原始问题聚焦于制作静态表情包梗图，sug词条中的“动图”是表情包的一种形式，属于辅助型延伸词，对原始问题有辅助作用，但非必需。\n【最终得分 0.41】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图cp_r2_q14_5": {
      "type": "sug",
      "query": "[SUG] 表情包梗图cp",
      "level": 23,
      "relevance_score": 0.17,
      "evaluationReason": "【评估对象】词条\"表情包梗图cp\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包、梗图\n【动机维度 0.00】原始问题是“制作”表情包梗图，sug词条「表情包梗图cp」缺失动作意图，无法判断其动机意图。故动机维度得分0分。\n【品类维度 0.25】原始问题对象层为「表情包梗图」，限定词为「人类双标行为」「猫咪」；sug词条对象层为「表情包梗图」，限定词为「cp」。对象层部分匹配，但sug词条限定词与原始问题完全不匹配，覆盖度低。\n【延伸词维度 -0.15】延伸词“cp”与原始问题中制作“反映人类双标行为的猫咪表情包梗图”的核心目的和作用域无关，引入了新的主题，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.17】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "sug_重返未来表情包梗图_r2_q14_6": {
      "type": "sug",
      "query": "[SUG] 重返未来表情包梗图",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"重返未来表情包梗图\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”，sug词条「重返未来表情包梗图」未体现任何明确的动作意图。因此，动机维度匹配度为0。\n【品类维度 0.05】sug词条仅包含原始问题中最宽泛的「表情包梗图」这一对象层，但原始问题的主体「猫咪」及场景层「反映人类双标行为」完全缺失。覆盖度极低，且核心主体完全不对应。\n【延伸词维度 -0.15】sug词条中的“重返未来”与原始问题中的“人类双标行为的猫咪表情包梗图”主题完全不符，引入了无关信息，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图可爱_r2_q14_7": {
      "type": "sug",
      "query": "[SUG] 表情包梗图可爱",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"表情包梗图可爱\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题的核心动机是“制作”。sug词条“表情包梗图可爱”缺乏明确的动作意图。因此，sug词条无法与原始问题的核心动机匹配。\n【品类维度 0.08】sug词是通用概念“表情包梗图”，原始问题是特定主题“反映人类双标行为的猫咪表情包梗图”。sug词过度泛化，未包含核心对象“猫咪”和限定词。\n【延伸词维度 -0.15】原始问题聚焦于「人类双标行为」和「猫咪表情包梗图」的结合，强调内容创作。sug词条「可爱」引入了与原始问题核心目的无关的审美维度，稀释了对「双标行为」这一主题的关注，降低了内容的针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图恶俗_r2_q14_8": {
      "type": "sug",
      "query": "[SUG] 表情包梗图恶俗",
      "level": 23,
      "relevance_score": -0.23,
      "evaluationReason": "【评估对象】词条\"表情包梗图恶俗\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的动机是「制作」表情包梗图，而sug词条中没有明确的动作意图。sug词条仅提及了表情包梗图的属性/评价，与原始问题的制作动机不匹配。\n【品类维度 -0.25】原始问题是关于“制作反映人类双标行为的猫咪表情包梗图”，sug词条“表情包梗图恶俗”虽有主体词“表情包梗图”，但增加了负面评价限定词“恶俗”，与原始问题的中性或偏创作意图不符，存在负向偏离。\n【延伸词维度 -0.15】延伸词“恶俗”与原始问题“制作反映人类双标行为的猫咪表情包梗图”的核心目的和作用域无关，反而引入了负面评价，稀释了用户对制作方法的关注，属于作用域稀释型。\n【最终得分 -0.23】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "sug_表情包梗图开心_r2_q14_9": {
      "type": "sug",
      "query": "[SUG] 表情包梗图开心",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"表情包梗图开心\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「表情包梗图开心」没有明确的动作意图。因此，sug词条未能体现原始问题的制作动机。\n【品类维度 0.08】原始问题需求是制作「反映人类双标行为的猫咪表情包梗图」，对象层是「猫咪表情包梗图」。sug词条只包含「表情包梗图」这个过度泛化的概念，缺失了「猫咪」这个核心限定词，且增加了无关的「开心」限定词，覆盖度低。\n【延伸词维度 -0.15】延伸词“开心”与原始问题“制作反映人类双标行为的猫咪表情包梗图”的核心目的和作用域无关，反而稀释了原始问题中“双标行为”这一特定主题的聚焦度，降低了内容的针对性。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.1755
    },
    "q_反映人类双标_r2_15": {
      "type": "q",
      "query": "[Q] 反映人类双标",
      "level": 22,
      "relevance_score": 0.0882,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_反映人类双胞胎基因变异_r2_q15_0": {
      "type": "sug",
      "query": "[SUG] 反映人类双胞胎基因变异",
      "level": 23,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"反映人类双胞胎基因变异\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是“制作表情包”，而sug词条中无明确的动作意图，因此无法匹配。\n【品类维度 -0.85】原始问题对象层为「猫咪表情包梗图」，场景层为「人类双标行为」。sug词条「人类双胞胎基因变异」在对象和场景上均与原始问题完全不匹配，是完全错误的品类。\n【延伸词维度 -0.60】sug词条中的“双胞胎基因变异”与原始问题中的“双标行为”在语义上完全不符，且“双胞胎基因变异”与“猫咪表情包梗图”也无关联，严重偏离了原始问题的核心主题和目的，属于作用域稀释型延伸词，且程度较深。\n【最终得分 -0.80】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0882
    },
    "q_反映人类双标行为_r2_16": {
      "type": "q",
      "query": "[Q] 反映人类双标行为",
      "level": 22,
      "relevance_score": 0.0882,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_反映人类双标行为的图片_r2_q16_0": {
      "type": "sug",
      "query": "[SUG] 反映人类双标行为的图片",
      "level": 23,
      "relevance_score": 0.44000000000000006,
      "evaluationReason": "【评估对象】词条\"反映人类双标行为的图片\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】sug词条「反映人类双标行为的图片」无明确动作意图，只提到了一个对象，未能体现原始问题中的核心动作「制作」。\n【品类维度 0.55】原始问题需求是「猫咪表情包梗图」，sug词条是「图片」。虽然sug覆盖了「反映人类双标行为」的场景限定，但核心对象「猫咪表情包梗图」与「图片」相比过于泛化，导致匹配度下降。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。原始问题中的“猫咪表情包梗图”被sug词条简化为“图片”，这属于原始问题对象层的泛化，不构成延伸词。\n【最终得分 0.44】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.0882
    },
    "q_人类双标行为_r2_17": {
      "type": "q",
      "query": "[Q] 人类双标行为",
      "level": 22,
      "relevance_score": 0.081,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_人类双标行为是什么意思_r2_q17_0": {
      "type": "sug",
      "query": "[SUG] 人类双标行为是什么意思",
      "level": 23,
      "relevance_score": -0.09500000000000001,
      "evaluationReason": "【评估对象】词条\"人类双标行为是什么意思\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「人类双标行为是什么意思」的动机是「了解/理解」一个概念。两者动机方向完全不一致。\n【品类维度 -0.20】原始问题主对象是“猫咪表情包梗图”，限定词是“反映人类双标行为”；sug词是“人类双标行为是什么意思”，主对象是“人类双标行为”，两者完全不匹配，sug词的限定词甚至在原始问题中是修饰成分。\n【延伸词维度 -0.15】延伸词“是什么意思”将原始问题从“制作”行为转变为“理解”概念，稀释了原始问题中“制作梗图”的核心目的，降低了内容针对性。\n【最终得分 -0.10】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.081
    },
    "q_双标行为_r2_18": {
      "type": "q",
      "query": "[Q] 双标行为",
      "level": 22,
      "relevance_score": 0.0765,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_双标行为举例_r2_q18_0": {
      "type": "sug",
      "query": "[SUG] 双标行为举例",
      "level": 23,
      "relevance_score": 0.21,
      "evaluationReason": "【评估对象】词条\"双标行为举例\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「双标行为举例」中没有明确的动作意图。\n【品类维度 0.30】原始问题核心是「猫咪表情包梗图」，限定词是「人类双标行为」。Sug词条仅包含「双标行为」，与原始问题的限定词部分重叠，但核心对象「猫咪表情包梗图」完全缺失，导致匹配度较低。\n【延伸词维度 -0.15】sug词条「双标行为举例」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的不符。原始问题侧重于“制作”和“猫咪表情包梗图”，而sug词条仅提供了“双标行为举例”，这属于原始问题中“双标行为”的背景知识，而非其核心动作或对象。它稀释了原始问题中“制作”和“表情包”的聚焦度，降低了内容针对性，属于作用域稀释型。\n【最终得分 0.21】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.0765
    },
    "sug_双标行为内涵是什么_r2_q18_1": {
      "type": "sug",
      "query": "[SUG] 双标行为内涵是什么",
      "level": 23,
      "relevance_score": -0.23,
      "evaluationReason": "【评估对象】词条\"双标行为内涵是什么\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】原始问题意图是「制作」反映人类双标行为的猫咪表情包梗图，sug词条「双标行为内涵是什么」意图是「了解」双标行为的内涵，两者动词不同，且sug词条无明确动机。\n【品类维度 -0.25】原始问题对象层包括“猫咪表情包梗图”和“人类双标行为”，场景层未明确。Sug词条对象层为“双标行为”，场景层不明确。原始问题询问制作方法而sug词条只涉及对“双标行为”的定义，品类不匹配且缺失核心对象“猫咪表情包梗图”。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，而sug词条「双标行为内涵是什么」将主题从「制作」转移到「概念解释」，稀释了原始问题的创作目的，属于作用域稀释型。\n【最终得分 -0.23】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "sug_讽刺双标的文案_r2_q18_2": {
      "type": "sug",
      "query": "[SUG] 讽刺双标的文案",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"讽刺双标的文案\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成（梗图）\n【动机维度 -0.15】原始问题的核心动机是「制作（梗图）」，sug词条的动机是「撰写/找寻（文案）」。两者动机存在部分重合，但方向上制作（图像）与撰写（文字）存在明显偏差。\n【品类维度 0.25】原始问题对象层为「猫咪表情包梗图」，场景层为「反映人类双标行为」。Sug词条对象层为「文案」，场景层为「讽刺双标」。场景层有部分匹配，但核心对象层「猫咪表情包梗图」与「文案」完全不符。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，延伸词「文案」虽然与「讽刺双标」相关，但偏离了「制作」和「猫咪表情包」的核心对象，引入了不相关的创作形式，稀释了原始问题的聚焦度。\n【最终得分 0.01】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "sug_王楚钦双标行为_r2_q18_3": {
      "type": "sug",
      "query": "[SUG] 王楚钦双标行为",
      "level": 23,
      "relevance_score": -0.7600000000000001,
      "evaluationReason": "【评估对象】词条\"王楚钦双标行为\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「王楚钦双标行为」仅是一个话题，不包含任何动作意图。因此，sug词条无法匹配原始问题的动机。\n【品类维度 -0.80】原始问题核心对象为「猫咪表情包梗图」与「人类双标行为」，强调「制作」。sug词条「王楚钦双标行为」对象为特定人物的「双标行为」。两者核心对象和限定词完全不匹配，品类冲突，属于负向偏离。\n【延伸词维度 -0.60】sug词条中的“王楚钦”和“双标行为”均是延伸词。“王楚钦”引入了与原始问题完全无关的人物，且“双标行为”脱离了原始问题中“猫咪表情包梗图”的创作语境，导致sug词条与原始问题核心目的完全偏离，严重稀释了原始问题的聚焦度。\n【最终得分 -0.76】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "sug_猫咪为什么会出现双标行为_r2_q18_4": {
      "type": "sug",
      "query": "[SUG] 猫咪为什么会出现双标行为",
      "level": 23,
      "relevance_score": -0.019999999999999997,
      "evaluationReason": "【评估对象】词条\"猫咪为什么会出现双标行为\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 -0.05】原始问题意图是「制作」表情包，sug词条是「探讨/理解」猫咪行为原因。两者意图方向不同，原始是创作行为，sug是知识探索行为，尽管主题相关，但动作意图相悖。\n【品类维度 0.05】原始问题核心对象是“表情包梗图”和“双标行为”，场景是“猫咪”。sug词条仅包含“猫咪”和“双标行为”这两个场景与主体，但它是一个现象的提问，而不是制作过程。内容，不匹配“表情包梗图”这个核心对象，因此匹配度低，但也不算有关联结到了一部分主体，是抽象相似。\n【延伸词维度 -0.15】原始问题是关于「制作」表情包梗图，核心是创作行为。sug词条「猫咪为什么会出现双标行为」将主题从创作转向了对猫咪行为的「解释」，引入了与原始问题核心目的无关的知识性探究，稀释了原始问题的聚焦度。\n【最终得分 -0.02】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "sug_双标男友的典型表现_r2_q18_5": {
      "type": "sug",
      "query": "[SUG] 双标男友的典型表现",
      "level": 23,
      "relevance_score": -0.43000000000000005,
      "evaluationReason": "【评估对象】词条\"双标男友的典型表现\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「双标男友的典型表现」并无明确动作意图，因此无法进行动作匹配，动机维度评分为0。\n【品类维度 -0.50】原始问题内容主体为《人类双标行为的猫咪表情包梗图》，sug词条内容主体为《双标男友的典型表现》。两者核心对象和限定词完全不匹配，品类完全冲突。\n【延伸词维度 -0.15】sug词条「双标男友」与原始问题中的「人类双标行为」在概念上有所关联，但将范围限定在「男友」这一特定人群，且未提及「猫咪表情包梗图」这一核心对象，导致原始问题的核心目的被稀释。\n【最终得分 -0.43】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "sug_猫咪双标行为搞笑视频_r2_q18_6": {
      "type": "sug",
      "query": "[SUG] 猫咪双标行为搞笑视频",
      "level": 23,
      "relevance_score": 0.33,
      "evaluationReason": "【评估对象】词条\"猫咪双标行为搞笑视频\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包/梗图\n【动机维度 0.25】原始问题核心动机是“制作”梗图，而sug词条是“视频”，两者形式不同且sug词条未体现制作意图。虽然都是内容创作（制作/拍摄），但sug词条未明确动作意图，因此匹配度较低。\n【品类维度 0.55】原始问题对象层为「猫咪表情包梗图」，场景层包括「人类双标行为」。sug词条对象层为「猫咪视频」，场景层包括「猫咪双标行为」「搞笑」。场景层「猫咪双标行为」与原始问题「人类双标行为」核心概念相似，但对象层「视频」与「表情包梗图」不符，有部分重叠。故评分为0.55。\n【延伸词维度 -0.15】原始问题聚焦于「表情包梗图」的制作，而sug词条引入了「搞笑视频」这一新的内容形式。这稀释了原始问题的核心目的，从制作静态图片转向了动态视频，降低了内容的针对性。\n【最终得分 0.33】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.0765
    },
    "sug_猫咪双标行为_r2_q18_7": {
      "type": "sug",
      "query": "[SUG] 猫咪双标行为",
      "level": 23,
      "relevance_score": 0.44000000000000006,
      "evaluationReason": "【评估对象】词条\"猫咪双标行为\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作，意图是产出表情包梗图\n【动机维度 0.00】原始问题明确意图是“制作”表情包梗图，而sug词条「猫咪双标行为」仅提供了制作的对象和主题，没有体现任何动作意图，因此动机维度评分为0。\n【品类维度 0.55】sug词条「猫咪双标行为」与原始问题「人类双标行为的猫咪表情包梗图」在对象层都包含「猫咪」和「双标行为」。原始问题还包含「表情包梗图」的核心对象和「人类」限定词，sug词条未涵盖。存在部分主体匹配和限定词匹配，但核心信息欠缺。\n【延伸词维度 0.00】sug词条未引入延伸词，所有词汇均属于原始问题作用域范围。\n【最终得分 0.44】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#22c55e",
      "parentQScore": 0.0765
    },
    "sug_双标是什么意思啊_r2_q18_8": {
      "type": "sug",
      "query": "[SUG] 双标是什么意思啊",
      "level": 23,
      "relevance_score": 0.0050000000000000044,
      "evaluationReason": "【评估对象】词条\"双标是什么意思啊\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作梗图，表达双标行为\n【动机维度 0.00】原始问题的核心动机是「制作」梗图，而sug词条「双标是什么意思啊」是「理解」或「查询」概念。sug词条与原始问题的制作动机完全不匹配。\n【品类维度 0.05】原始问题需求是制作猫咪双标行为表情包梗图，对象层有「双标行为」和「猫咪表情包梗图」。sug词条只涉及了「双标」这一概念，对象层和场景层覆盖度极低。\n【延伸词维度 -0.15】sug词条「双标是什么意思啊」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符。原始问题是关于创作和制作，而sug词条是关于概念解释，引入了无关信息，稀释了原始问题的聚焦度，降低了内容的针对性。\n【最终得分 0.01】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "sug_双标的人怎么怼_r2_q18_9": {
      "type": "sug",
      "query": "[SUG] 双标的人怎么怼",
      "level": 23,
      "relevance_score": -0.17500000000000004,
      "evaluationReason": "【评估对象】词条\"双标的人怎么怼\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「怎么怼」意图是「反击/对抗」。两者动作意图完全不匹配。\n【品类维度 -0.40】原始问题内容主体为「人类双标行为」和「猫咪表情包梗图」，sug词条内容主体为「双标的人」。sug只有「双标」相关概念，缺少「猫咪表情包梗图」这一核心对象，且sug词侧重于互动反驳，与原始问题制作内容的主体含义有较大差异，存在品类错位。\n【延伸词维度 -0.15】sug词条「双标的人怎么怼」中的“怼”是延伸词，它引入了与原始问题“制作表情包梗图”完全不相关的行为，稀释了原始问题的创作和表达目的，偏离了核心需求。\n【最终得分 -0.18】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0765
    },
    "q_反映人类_r2_19": {
      "type": "q",
      "query": "[Q] 反映人类",
      "level": 22,
      "relevance_score": 0.0702,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_反映人类社会发展进步的价值理念_r2_q19_0": {
      "type": "sug",
      "query": "[SUG] 反映人类社会发展进步的价值理念",
      "level": 23,
      "relevance_score": -0.7600000000000001,
      "evaluationReason": "【评估对象】词条\"反映人类社会发展进步的价值理念\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”，而sug词条「反映人类社会发展进步的价值理念」中没有明确的动作意图。sug词条无动机，因此动机维度评分为0。\n【品类维度 -0.80】原始问题核心对象是《猫咪表情包梗图》，限定词是《人类双标行为》。sug词条核心对象是《价值理念》，限定词是《人类社会发展进步》，两者在对象和限定词上均无任何匹配，品类完全冲突。\n【延伸词维度 -0.60】sug词条中的“社会发展进步的价值理念”与原始问题中的“人类双标行为的猫咪表情包梗图”完全不相关，引入了与原始问题核心目的和作用域完全无关的宏大主题，严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.76】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_人类图反映者_r2_q19_1": {
      "type": "sug",
      "query": "[SUG] 人类图反映者",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"人类图反映者\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是“制作”表情包梗图。sug词条「人类图反映者」不包含任何动作意图，因此无法与原始问题的动作意图进行匹配。\n【品类维度 -0.20】原始问题核心对象是“猫咪表情包梗图”和“双标行为”，场景限定“人类”。Sug词是“人类图反映者”，对象完全不匹配，不具备相关性，存在误导性。\n【延伸词维度 -0.15】sug词条「人类图反映者」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和对象完全不符，引入了无关概念，稀释了原始问题的聚焦度。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_怎么识别人类图中的反映者_r2_q19_2": {
      "type": "sug",
      "query": "[SUG] 怎么识别人类图中的反映者",
      "level": 23,
      "relevance_score": -0.09500000000000001,
      "evaluationReason": "【评估对象】词条\"怎么识别人类图中的反映者\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图），内容是反映双标行为\n【动机维度 0.00】原始问题的核心动机是《制作》表情包梗图，而sug词条的核心动机是《识别》人类图像中的反映者。两者动机完全不匹配，无任何关联。\n【品类维度 -0.20】原始问题核心是「猫咪表情包梗图」这一对象和「人类双标行为」这一场景限定。sug词条「识别人类图中的反映者」与原始问题对象层和场景层均不匹配，二者核心主体完全不同，存在品类错位。\n【延伸词维度 -0.15】sug词条中的“识别人类图中的反映者”与原始问题“制作反映人类双标行为的猫咪表情包梗图”的核心目的和作用域完全不符，引入了无关的识别概念，稀释了原始问题关于“制作”和“猫咪表情包”的聚焦度，属于作用域稀释型。\n【最终得分 -0.10】",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_人类图显示者_r2_q19_3": {
      "type": "sug",
      "query": "[SUG] 人类图显示者",
      "level": 23,
      "relevance_score": -0.52,
      "evaluationReason": "【评估对象】词条\"人类图显示者\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，而sug词条「人类图显示者」无法识别出任何动作意图，因此动机匹配度为0。\n【品类维度 -0.50】原始问题核心对象是「猫咪表情包梗图」及「人类双标行为」内容。Sug词「人类图显示者」是完全不相关的概念。核心对象和内容主体均完全不匹配，品类冲突。\n【延伸词维度 -0.60】sug词条「人类图显示者」与原始问题「制作反映人类双标行为的猫咪表情包梗图」完全不相关，属于作用域无关型，且严重偏离原始问题，稀释了原始问题的核心目的。\n【最终得分 -0.52】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_人类图解读_r2_q19_4": {
      "type": "sug",
      "query": "[SUG] 人类图解读",
      "level": 23,
      "relevance_score": -0.8,
      "evaluationReason": "【评估对象】词条\"人类图解读\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题核心动机是「制作」表情包，而Sug词条「人类图解读」不包含任何明确的动机，因此无法匹配。\n【品类维度 -0.85】原始问题意在生成「猫咪表情包梗图」，对象和场景为「猫咪」和「表情包梗图」。sug词为「人类图解读」，与原始问题中的核心主体「猫咪」和「表情包梗图」完全不匹配，是完全不同的概念类别，属于负向偏离。\n【延伸词维度 -0.60】原始问题聚焦于制作「猫咪表情包梗图」以反映「人类双标行为」，核心是内容创作和主题表达。「人类图解读」是一个完全不相关的概念，与原始问题的动机、对象、场景均无关联，属于严重的稀释型延伸词，将用户引导至完全不同的领域，对原始问题目的达成造成负面影响。\n【最终得分 -0.80】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_人类图是什么_r2_q19_5": {
      "type": "sug",
      "query": "[SUG] 人类图是什么",
      "level": 23,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"人类图是什么\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题动机是“制作表情包”，sug词条“人类图是什么”的动机是“了解/学习”某个概念，两者动作意图完全不匹配。\n【品类维度 -0.80】原始问题核心对象是《人类双标行为的猫咪表情包梗图》，场景限定涉及《人类双标行为》。sug词条《人类图是什么》的核心对象是《人类图》，两者在品类上完全不符，主体词和限定词均无关联。\n【延伸词维度 -0.60】sug词条「人类图」与原始问题「制作反映人类双标行为的猫咪表情包梗图」在主题和目的上完全不相关，引入了与原始问题核心需求无关的全新概念，严重稀释了原始问题的聚焦度，导致内容偏离，属于作用域稀释型。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_反映者适合什么工作_r2_q19_6": {
      "type": "sug",
      "query": "[SUG] 反映者适合什么工作",
      "level": 23,
      "relevance_score": -0.38000000000000006,
      "evaluationReason": "【评估对象】词条\"反映者适合什么工作\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是\"制作\"表情包梗图。sug词条「反映者适合什么工作」的动机是\"适合\"或\"寻找\"工作。两者动作完全不匹配且无关。\n【品类维度 -0.80】原始问题核心是「人类双标行为」「猫咪表情包梗图」，sug词条是「反映者适合什么工作」。两者对象层和场景层均完全不匹配，是完全不同的话题领域。\n【延伸词维度 -0.60】sug词条「反映者适合什么工作」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」完全不相关，引入了与原始问题制作表情包梗图完全无关的职业选择话题，严重稀释了原始问题的聚焦度。\n【最终得分 -0.38】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_人类图投射者_r2_q19_7": {
      "type": "sug",
      "query": "[SUG] 人类图投射者",
      "level": 23,
      "relevance_score": -0.7100000000000001,
      "evaluationReason": "【评估对象】词条\"人类图投射者\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题意图是「制作」表情包，sug词条「人类图投射者」仅为名词短语，不包含任何动作意图，因此无法评估动作匹配度。\n【品类维度 -0.85】原始问题核心是制作「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词是「人类图投射者」，两者在核心对象和限定词上完全不匹配，品类差异巨大。\n【延伸词维度 -0.15】sug词条「人类图投射者」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符，引入了无关概念，稀释了原始问题的聚焦度。\n【最终得分 -0.71】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_反映者的代表人物_r2_q19_8": {
      "type": "sug",
      "query": "[SUG] 反映者的代表人物",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"反映者的代表人物\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包、梗图），表达/展现（反映人类双标行为）\n【动机维度 0.00】原始问题的核心动机是“制作”猫咪梗图以“反映”人类行为。sug词条「反映者的代表人物」中，动词“反映”与原始问题中的“反映”存在字面重叠，但sug词条没有明确的动机意图，因此无法评估动机匹配度。\n【品类维度 -0.20】原始问题核心对象是《猫咪表情包梗图》，限定词包括《人类双标行为》、《制作》。sug词《反映者的代表人物》与原始问题对象与限定词完全不符，品类错位。\n【延伸词维度 -0.15】原始问题聚焦于「制作」猫咪表情包梗图，而sug词条「反映者的代表人物」引入了与制作行为无关的人物概念，稀释了原始问题的核心目的，属于作用域稀释型。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "sug_人类图测试_r2_q19_9": {
      "type": "sug",
      "query": "[SUG] 人类图测试",
      "level": 23,
      "relevance_score": -0.3350000000000001,
      "evaluationReason": "【评估对象】词条\"人类图测试\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作/生成（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是\"制作/生成\"，而sug词条\"人类图测试\"的动机是\"测试\"。二者动机没有相关性。\n【品类维度 -0.80】原始问题集中在「猫咪表情包梗图」的制作，兼含「人类双标行为」限定。sug词条「人类图测试」与核心主体「表情包梗图」和限定词均无关联，品类严重不匹配。\n【延伸词维度 -0.15】原始问题是关于制作猫咪表情包梗图以反映人类双标行为，核心是「制作」和「猫咪表情包梗图」。sug词条「人类图测试」引入了与原始问题完全不相关的概念「人类图测试」，既不属于原始问题的任何作用域，也无助于原始目的的达成，反而稀释了原始问题的聚焦度。\n【最终得分 -0.34】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "q_反映人类行为_r2_20": {
      "type": "q",
      "query": "[Q] 反映人类行为",
      "level": 22,
      "relevance_score": 0.0702,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_反映人类行为的环境问题_r2_q20_0": {
      "type": "sug",
      "query": "[SUG] 反映人类行为的环境问题",
      "level": 23,
      "relevance_score": -0.27599999999999997,
      "evaluationReason": "【评估对象】词条\"反映人类行为的环境问题\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作\n【动机维度 0.00】sug词条缺乏明确的动作意图和目的性，无法评估动作匹配度。原始问题的核心动作是「制作」，而sug词条没有表现出任何动作意图。\n【品类维度 -0.30】原始问题核心对象为「猫咪表情包梗图」，限定词为「人类双标行为」。sug词条核心对象为「环境问题」，限定词为「人类行为」，两者对象不匹配且限定词差异大，存在品类冲突。\n【延伸词维度 -0.18】sug词条中的“环境问题”是延伸词，它与原始问题中的“人类双标行为”和“猫咪表情包梗图”完全不相关，严重稀释了原始问题的聚焦度，导致内容偏离核心。\n【最终得分 -0.28】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.0702
    },
    "q_人类行为_r2_21": {
      "type": "q",
      "query": "[Q] 人类行为",
      "level": 22,
      "relevance_score": 0.045,
      "evaluationReason": "",
      "strategy": "Query",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "domain_index": -1,
      "domain_type": "D2"
    },
    "sug_人类行为与社会环境_r2_q21_0": {
      "type": "sug",
      "query": "[SUG] 人类行为与社会环境",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"人类行为与社会环境\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】sug词条「人类行为与社会环境」是纯名词性短语，无法识别出任何明确的动作意图。因此，无法与原始问题「制作」的动作意图进行匹配。\n【品类维度 -0.20】原始问题核心对象是《猫咪表情包梗图》，限定词是《人类双标行为》。sug词《人类行为与社会环境》只在《人类行为》上与原始问题概念有弱关联，但sug词本身过于泛化且缺少核心对象和场景，无法匹配。\n【延伸词维度 -0.15】原始问题聚焦于「制作猫咪表情包梗图」这一具体行为，并限定了主题「反映人类双标行为」。sug词条「人类行为与社会环境」是高度概括的学术概念，与原始问题的具体制作需求和娱乐属性不符，稀释了原始问题的聚焦度，使其偏离了核心目的。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为设计师-小周_r2_q21_1": {
      "type": "sug",
      "query": "[SUG] 人类行为设计师-小周",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"人类行为设计师-小周\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题意图是「制作」表情包梗图，sug词条「人类行为设计师-小周」并未包含动作意图，因此无法匹配。\n【品类维度 -0.20】原始问题内容主题是“猫咪表情包梗图”，限定词是“反映人类双标行为”；sug词条是“人类行为设计师-小周”，内容主题和限定词均与原始问题无关且无关，仅有「人类行为」弱关联，但sug是人物而sug是职业主体词错位\n【延伸词维度 -0.15】sug词条「人类行为设计师-小周」与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」的核心目的和作用域完全不符。它引入了一个与表情包制作、猫咪、双标行为等核心概念无关的职业和人名，严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为与社会环境重点_r2_q21_2": {
      "type": "sug",
      "query": "[SUG] 人类行为与社会环境重点",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"人类行为与社会环境重点\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图。sug词条「人类行为与社会环境重点」仅是名词短语，无任何动作意图，因此动机匹配度为0。\n【品类维度 -0.20】原始问题涉及「猫咪表情包梗图」这一对象，限定词是「人类双标行为」。sug词主对象是「人类行为与社会环境」，与原始问题的主要对象「表情包梗图」完全不符，但二者都含有「人类行为」这一概念，sug词的限定词「社会环境重点」完全不匹配，与原始问题不相关，有一定偏离\n【延伸词维度 -0.15】原始问题聚焦于「制作猫咪表情包梗图」以「反映人类双标行为」，而sug词条「人类行为与社会环境重点」则是一个宽泛的学术领域，与制作表情包这一具体操作和猫咪主题完全无关，属于作用域稀释型延伸词，严重偏离了原始问题的核心目的和对象。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为与社会环境笔记_r2_q21_3": {
      "type": "sug",
      "query": "[SUG] 人类行为与社会环境笔记",
      "level": 23,
      "relevance_score": -0.7100000000000001,
      "evaluationReason": "【评估对象】词条\"人类行为与社会环境笔记\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作（表情包梗图）\n【动机维度 0.00】原始问题的核心动机是【制作】表情包梗图，sug词条「人类行为与社会环境笔记」无明确的动作意图。\n【品类维度 -0.85】原始问题核心对象是《猫咪表情包梗图》，限定词有《人类双标行为》。sug词条核心对象是《人类行为与社会环境笔记》，与原始问题的核心对象完全不符，品类严重冲突。\n【延伸词维度 -0.15】sug词条「人类行为与社会环境笔记」中的“笔记”是延伸词，它与原始问题「如何制作反映人类双标行为的猫咪表情包梗图」中的“制作”和“梗图”无关，稀释了原始问题的聚焦度，降低了内容针对性。\n【最终得分 -0.71】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为矫正教育漫画_r2_q21_4": {
      "type": "sug",
      "query": "[SUG] 人类行为矫正教育漫画",
      "level": 23,
      "relevance_score": -0.21500000000000002,
      "evaluationReason": "【评估对象】词条\"人类行为矫正教育漫画\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「人类行为矫正教育漫画」的动机是「矫正」和「教育」。两者动机意图完全不匹配。\n【品类维度 -0.50】原始问题核心对象是“猫咪表情包梗图”，限定词是“人类双标行为”。Sug词条是“人类行为矫正教育漫画”，其核心对象和限定词与原始问题完全不匹配，品类冲突严重。\n【延伸词维度 -0.15】原始问题聚焦于「制作猫咪表情包梗图」以反映「人类双标行为」，核心是内容创作和主题表达。「人类行为矫正教育漫画」中的「矫正教育」和「漫画」与原始问题的「制作表情包梗图」和「反映双标行为」存在较大偏差，稀释了原始问题的创作性和娱乐性，引入了教育和矫正的无关维度。\n【最终得分 -0.22】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为与社会环境第三版_r2_q21_5": {
      "type": "sug",
      "query": "[SUG] 人类行为与社会环境第三版",
      "level": 23,
      "relevance_score": -0.7600000000000001,
      "evaluationReason": "【评估对象】词条\"人类行为与社会环境第三版\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】原始问题的核心动机是\"制作\"表情包梗图，表达一种创造和产出的意图。它涉及到创作过程中的技能运用和结果产出。\n【动机维度 0.00】原始问题的动机是创造和产出（制作），而sug词条无法识别出明确的动作意图（名词性词条），因此无法进行动作上的匹配。\n【品类维度 -0.80】原始问题核心对象是“猫咪表情包梗图”和“双标行为”，场景限定为“人类”。sug词条是“人类行为与社会环境第三版”，属于学术书籍，对象和场景都与原始问题完全不匹配，是明显错误的品类。\n【延伸词维度 -0.60】sug词条「人类行为与社会环境第三版」与原始问题「制作猫咪表情包梗图」完全不相关，属于作用域无关型延伸词，且严重偏离原始问题核心，稀释了用户意图。\n【最终得分 -0.76】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20% + 规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为矫正教育_r2_q21_6": {
      "type": "sug",
      "query": "[SUG] 人类行为矫正教育",
      "level": 23,
      "relevance_score": -0.7350000000000001,
      "evaluationReason": "【评估对象】词条\"人类行为矫正教育\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 -0.80】原始问题的核心动机是“制作”特定主题（反映人类双标行为的猫咪表情包梗图），而sug词条「人类行为矫正教育」的动机是“教育”或“矫正”。两者动作意图完全不匹配，甚至方向相反，因此得分较低。\n【品类维度 -0.80】原始问题核心对象为「猫咪表情包梗图」，限定词为「反映人类双标行为」。sug词为「人类行为矫正教育」。两者对象、限定词均无匹配，品类完全不同且偏离严重。\n【延伸词维度 -0.15】sug词条「人类行为矫正教育」与原始问题「制作猫咪表情包梗图」的核心目的完全不符，引入了与原始问题无关的全新主题，严重稀释了原始问题的聚焦度，导致内容偏离。\n【最终得分 -0.74】\n【规则说明】规则3：核心维度严重负向，上限=0",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为心理学_r2_q21_7": {
      "type": "sug",
      "query": "[SUG] 人类行为心理学",
      "level": 23,
      "relevance_score": 0.010000000000000009,
      "evaluationReason": "【评估对象】词条\"人类行为心理学\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包\n【动机维度 0.00】原始问题的核心动机是「制作」表情包，而Sug词条「人类行为心理学」无明确的动作意图。\n【品类维度 0.05】原始问题核心是制作《猫咪表情包梗图》，作用域侧重内容创作与娱乐。sug词条《人类行为心理学》是偏学术的理论知识，虽与行为有弱关联，但品类差异大，覆盖度低，相关性很弱。\n【延伸词维度 -0.15】原始问题聚焦于「制作表情包梗图」这一具体创作行为，并限定了主题「人类双标行为的猫咪表情包」。sug词条「人类行为心理学」是一个宽泛的学术领域，与制作表情包的实践性需求关联度低，且未能体现猫咪和表情包的创作元素，稀释了原始问题的聚焦度。\n【最终得分 0.01】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为观察员_r2_q21_8": {
      "type": "sug",
      "query": "[SUG] 人类行为观察员",
      "level": 23,
      "relevance_score": 0.034,
      "evaluationReason": "【评估对象】词条\"人类行为观察员\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】制作表情包梗图\n【动机维度 0.00】原始问题的核心动机是「制作」表情包梗图，而sug词条「人类行为观察员」没有包含任何动作意图，因此动机匹配度为0。\n【品类维度 0.08】原始问题涉及“人类行为”和“猫咪表情包梗图”，sug词条仅包含“人类行为”这一部分，且表达过于概括、抽象，没有提及猫咪、表情包等核心限定，覆盖度低。\n【延伸词维度 -0.15】sug词条「人类行为观察员」与原始问题「制作反映人类双标行为的猫咪表情包梗图」的核心目的和对象均不符。它引入了一个与制作表情包无关的新主题，稀释了原始问题的聚焦度，属于作用域稀释型。\n【最终得分 0.03】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "sug_人类行为艺术_r2_q21_9": {
      "type": "sug",
      "query": "[SUG] 人类行为艺术",
      "level": 23,
      "relevance_score": -0.19000000000000003,
      "evaluationReason": "【评估对象】词条\"人类行为艺术\" vs 原始问题\"如何制作反映人类双标行为的猫咪表情包梗图\"\n【核心动机】「制作」反映人类双标行为的猫咪表情包梗图\n【动机维度 0.00】原始问题意图是「制作」特定表情包梗图，sug词条「人类行为艺术」没有明确的动作意图。因此，sug词条缺失动机层，无法评估动作匹配度。\n【品类维度 -0.20】原始问题核心是《猫咪表情包梗图》体现《人类双标行为》，sug词条《人类行为艺术》与原始问题主体《猫咪表情包梗图》品类不符，且限定词差异大。\n【延伸词维度 -0.15】sug词条「人类行为艺术」与原始问题「猫咪表情包梗图」的核心对象和目的完全不符，稀释了原始问题的聚焦度，使其偏离核心。\n【最终得分 -0.19】\n【规则说明】情况3：sug词条无动作意图，权重调整为 品类80% + 延伸词20%",
      "strategy": "推荐词",
      "iteration": 2,
      "is_selected": true,
      "scoreColor": "#ef4444",
      "parentQScore": 0.045
    },
    "step_comb_r2": {
      "type": "step",
      "query": "步骤2: 跨2个域组合 (149个组合)",
      "level": 21,
      "relevance_score": 0,
      "strategy": "域内组词",
      "iteration": 2,
      "is_selected": true
    },
    "comb_如何反映_r2_0": {
      "type": "domain_combination",
      "query": "如何反映",
      "level": 22,
      "relevance_score": 0.03408,
      "evaluationReason": "【Round 2+ 域间评估】\n【评估对象】组合\"如何反映\"\n【评估对象】词条\"如何反映\" vs 作用域词条\"如何反映人类双标行为的\"\n【核心动机】反映\n【动机维度 0.98】词条的核心动作“反映”与原始问题的核心动作“反映”完全一致。\n【品类维度 0.08】词条“如何反映”是一个通用概念，而同一作用域词条“如何反映人类双标行为的”是一个特定概念。词条仅包含同一作用域词条中的动词部分，没有包含任何名词或限定词，因此品类匹配度极低，但由于动词部分相同，给予极低的正分。\n【最终得分 0.71】\n【规则说明】规则A：动机高分保护生效（动机0.98≥0.8），实际得分0.71已≥0.7\n【加权系数计算】\n0.048\n  来源词总得分: 0.05\n  系数: 0.05【计算公式】base_score × 系数 = 0.71 × 0.05\n【最终得分（截断后）】0.03",
      "strategy": "域内组合",
      "iteration": 2,
      "is_selected": true,
      "type_label": "[疑问引导+修饰短语]",
      "source_words": [
        [
          "如何"
        ],
        [
          "反映"
        ]
      ],
      "from_segments": [
        "如何",
        "反映人类双标行为的"
      ],
      "domains": [
        0,
        2
      ],
      "domains_str": "D0,D2",
      "source_word_details": [
        {
          "domain_index": 0,
          "segment_type": "疑问引导",
          "segment_text": "如何",
          "words": [
            {
              "text": "如何",
              "score": 0.024
            }
          ]
        },
        {
          "domain_index": 2,
          "segment_type": "修饰短语",
          "segment_text": "反映人类双标行为的",
          "words": [
            {
              "text": "反映",
              "score": 0.024
            }
          ]
        }
      ],
      "source_scores": [
        0.024,
        0.024
      ],
      "is_above_sources": true,
      "max_source_score": 0.024,
      "scoreColor": "#22c55e"
    },
    "comb_如何人类_r2_1": {
      "type": "domain_combination",
      "query": "如何人类",
      "level": 22,
      "relevance_score": 0.001152,
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      "knowledge_reason": "帖子正文仅表示可以私拿原图和自制表情包，并无提供任何关于表情包制作的方法、技巧、工具使用或流程步骤等具体创作知识。",
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      "iteration": 2,
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      "query": "[Q] 猫咪表情包制作",
      "level": 22,
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      "iteration": 2,
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      "suggestion_label": "[suggestion]"
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    "next_round_可爱又双标的表情包_r2_40": {
      "type": "next_round_item",
      "query": "[Q] 可爱又双标的表情包",
      "level": 22,
      "relevance_score": 0.68,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_怼双标的人表情包_r2_41": {
      "type": "next_round_item",
      "query": "[Q] 怼双标的人表情包",
      "level": 22,
      "relevance_score": 0.655,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图meme原创_r2_42": {
      "type": "next_round_item",
      "query": "[Q] 梗图meme原创",
      "level": 22,
      "relevance_score": 0.654,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包梗图搞笑_r2_43": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包梗图搞笑",
      "level": 22,
      "relevance_score": 0.6000000000000001,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包图片_r2_44": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包图片",
      "level": 22,
      "relevance_score": 0.52,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包图片_r2_45": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包图片",
      "level": 22,
      "relevance_score": 0.52,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_讽刺双标的图片_r2_46": {
      "type": "next_round_item",
      "query": "[Q] 讽刺双标的图片",
      "level": 22,
      "relevance_score": 0.49,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_讽刺双标的图片_r2_47": {
      "type": "next_round_item",
      "query": "[Q] 讽刺双标的图片",
      "level": 22,
      "relevance_score": 0.49,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_双标表情包图片_r2_48": {
      "type": "next_round_item",
      "query": "[Q] 双标表情包图片",
      "level": 22,
      "relevance_score": 0.48,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包_r2_49": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包",
      "level": 22,
      "relevance_score": 0.48,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图描改过程_r2_50": {
      "type": "next_round_item",
      "query": "[Q] 梗图描改过程",
      "level": 22,
      "relevance_score": 0.46,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包视频_r2_51": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包视频",
      "level": 22,
      "relevance_score": 0.455,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪搞笑表情包_r2_52": {
      "type": "next_round_item",
      "query": "[Q] 猫咪搞笑表情包",
      "level": 22,
      "relevance_score": 0.44999999999999996,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_反映人类双标行为的图片_r2_53": {
      "type": "next_round_item",
      "query": "[Q] 反映人类双标行为的图片",
      "level": 22,
      "relevance_score": 0.44000000000000006,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪双标行为_r2_54": {
      "type": "next_round_item",
      "query": "[Q] 猫咪双标行为",
      "level": 22,
      "relevance_score": 0.44000000000000006,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图素材抽象_r2_55": {
      "type": "next_round_item",
      "query": "[Q] 梗图素材抽象",
      "level": 22,
      "relevance_score": 0.41000000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪咪表情包图片_r2_56": {
      "type": "next_round_item",
      "query": "[Q] 猫咪咪表情包图片",
      "level": 22,
      "relevance_score": 0.41000000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包动图_r2_57": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包动图",
      "level": 22,
      "relevance_score": 0.41000000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_表情包梗图动图_r2_58": {
      "type": "next_round_item",
      "query": "[Q] 表情包梗图动图",
      "level": 22,
      "relevance_score": 0.41000000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图素材表情包_r2_59": {
      "type": "next_round_item",
      "query": "[Q] 梗图素材表情包",
      "level": 22,
      "relevance_score": 0.4,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪梗图素材_r2_60": {
      "type": "next_round_item",
      "query": "[Q] 猫咪梗图素材",
      "level": 22,
      "relevance_score": 0.4,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪梗图模板_r2_61": {
      "type": "next_round_item",
      "query": "[Q] 猫咪梗图模板",
      "level": 22,
      "relevance_score": 0.4,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_表情包梗图学习_r2_62": {
      "type": "next_round_item",
      "query": "[Q] 表情包梗图学习",
      "level": 22,
      "relevance_score": 0.39499999999999996,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包配文_r2_63": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包配文",
      "level": 22,
      "relevance_score": 0.38,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图meme素材_r2_64": {
      "type": "next_round_item",
      "query": "[Q] 梗图meme素材",
      "level": 22,
      "relevance_score": 0.37,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪表情包可爱_r2_65": {
      "type": "next_round_item",
      "query": "[Q] 猫咪表情包可爱",
      "level": 22,
      "relevance_score": 0.37,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_表情包梗图抽象_r2_66": {
      "type": "next_round_item",
      "query": "[Q] 表情包梗图抽象",
      "level": 22,
      "relevance_score": 0.37,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫meme表情包动图_r2_67": {
      "type": "next_round_item",
      "query": "[Q] 猫meme表情包动图",
      "level": 22,
      "relevance_score": 0.36,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪梗图骂人_r2_68": {
      "type": "next_round_item",
      "query": "[Q] 猫咪梗图骂人",
      "level": 22,
      "relevance_score": 0.34500000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图模版表情包_r2_69": {
      "type": "next_round_item",
      "query": "[Q] 梗图模版表情包",
      "level": 22,
      "relevance_score": 0.33000000000000007,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪梗图伤感_r2_70": {
      "type": "next_round_item",
      "query": "[Q] 猫咪梗图伤感",
      "level": 22,
      "relevance_score": 0.33000000000000007,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪双标行为搞笑视频_r2_71": {
      "type": "next_round_item",
      "query": "[Q] 猫咪双标行为搞笑视频",
      "level": 22,
      "relevance_score": 0.33,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪梗图拍照_r2_72": {
      "type": "next_round_item",
      "query": "[Q] 猫咪梗图拍照",
      "level": 22,
      "relevance_score": 0.29999999999999993,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_双标搞笑图片_r2_73": {
      "type": "next_round_item",
      "query": "[Q] 双标搞笑图片",
      "level": 22,
      "relevance_score": 0.29000000000000004,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_猫咪梗图英文_r2_74": {
      "type": "next_round_item",
      "query": "[Q] 猫咪梗图英文",
      "level": 22,
      "relevance_score": 0.29000000000000004,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_梗图描改模板_r2_75": {
      "type": "next_round_item",
      "query": "[Q] 梗图描改模板",
      "level": 22,
      "relevance_score": 0.28500000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_双标梗_r2_76": {
      "type": "next_round_item",
      "query": "[Q] 双标梗",
      "level": 22,
      "relevance_score": 0.27999999999999997,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_暗示双标的图片_r2_77": {
      "type": "next_round_item",
      "query": "[Q] 暗示双标的图片",
      "level": 22,
      "relevance_score": 0.24999999999999997,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_meme梗图分享_r2_78": {
      "type": "next_round_item",
      "query": "[Q] meme梗图分享",
      "level": 22,
      "relevance_score": 0.21000000000000002,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_双标行为举例_r2_79": {
      "type": "next_round_item",
      "query": "[Q] 双标行为举例",
      "level": 22,
      "relevance_score": 0.21,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_双标_r2_80": {
      "type": "next_round_item",
      "query": "[Q] 双标",
      "level": 22,
      "relevance_score": 0.2,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    },
    "next_round_表情包图片大全素材_r2_81": {
      "type": "next_round_item",
      "query": "[Q] 表情包图片大全素材",
      "level": 22,
      "relevance_score": 0.19400000000000003,
      "strategy": "高增益SUG",
      "iteration": 2,
      "is_selected": true,
      "type_label": "",
      "item_type": "sug",
      "is_suggestion": true,
      "suggestion_label": "[suggestion]"
    }
  },
  "edges": [
    {
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      "edge_type": "round_to_step",
      "strategy": "分段"
    },
    {
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      "to": "segment_0_r0",
      "edge_type": "step_to_segment",
      "strategy": "疑问引导"
    },
    {
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      "to": "word_如何_seg0_0",
      "edge_type": "segment_to_word",
      "strategy": "Word"
    },
    {
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      "strategy": "核心动作"
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    },
    {
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      "to": "segment_2_r0",
      "edge_type": "step_to_segment",
      "strategy": "修饰短语"
    },
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      "to": "word_反映_seg2_0",
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    },
    {
      "from": "segment_2_r0",
      "to": "word_人类_seg2_1",
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    },
    {
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      "to": "word_双标_seg2_2",
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    },
    {
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      "edge_type": "step_to_segment",
      "strategy": "中心名词"
    },
    {
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      "to": "word_猫咪_seg3_0",
      "edge_type": "segment_to_word",
      "strategy": "Word"
    },
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      "to": "word_表情包_seg3_1",
      "edge_type": "segment_to_word",
      "strategy": "Word"
    },
    {
      "from": "segment_3_r0",
      "to": "word_梗图_seg3_2",
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      "strategy": "Word"
    },
    {
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      "to": "round_1",
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    {
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      "to": "step_sug_r1",
      "edge_type": "round_to_step",
      "strategy": "推荐词"
    },
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      "search_制作表情包_r1_0",
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      "next_round_猫咪表情包梗图_r1_0",
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    "13": [
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      "sug_如何快速挣到钱_r1_q0_2",
      "sug_如何和女生聊天找话题_r1_q0_3",
      "sug_如何快速入睡_r1_q0_4",
      "sug_如何让男生持续上头_r1_q0_5",
      "sug_如何逼自己自律学习_r1_q0_6",
      "sug_如何连接别人家的加密wifi_r1_q0_7",
      "sug_如何养好头发_r1_q0_8",
      "sug_如何治疗早泻时间短_r1_q0_9",
      "sug_制作ppt_r1_q1_0",
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      "sug_制作冰糖葫芦_r1_q1_2",
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      "sug_制作美食_r1_q1_5",
      "sug_制作简历_r1_q1_6",
      "sug_制作饮品_r1_q1_7",
      "sug_制作小房子_r1_q1_8",
      "sug_制作表格_r1_q1_9",
      "sug_反映问题还是反应问题_r1_q2_0",
      "sug_反映和反应的区别_r1_q2_1",
      "sug_反映是什么意思_r1_q2_2",
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      "sug_反映财务状况的会计要素_r1_q2_7",
      "sug_反映的英语_r1_q2_8",
      "sug_反映事物间的互补关系_r1_q2_9",
      "sug_人类一败涂地_r1_q3_0",
      "sug_人类狗窝_r1_q3_1",
      "sug_人类幼崽陪伴指南_r1_q3_2",
      "sug_人类用沙想捏出梦里通天塔_r1_q3_3",
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      "sug_人类进化史_r1_q3_6",
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      "sug_双椒兔做法_r1_q4_6",
      "sug_双标图片_r1_q4_7",
      "sug_双标表情包_r1_q4_8",
      "sug_双标的人_r1_q4_9",
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      "sug_行为规范家_r1_q5_9",
      "sug_猫咪领养免费领养_r1_q6_0",
      "sug_猫咪叫声吸引小猫_r1_q6_1",
      "sug_猫咪呕吐_r1_q6_2",
      "sug_猫咪头像_r1_q6_3",
      "sug_猫咪取名_r1_q6_4",
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      "sug_猫咪搞笑视频_r1_q6_6",
      "sug_猫咪叫声_r1_q6_7",
      "sug_猫咪驱虫药推荐_r1_q6_8",
      "sug_猫咪黑下巴怎么处理_r1_q6_9",
      "sug_表情包抽象_r1_q7_0",
      "sug_表情包怎么制作_r1_q7_1",
      "sug_表情包可爱_r1_q7_2",
      "sug_表情包图片大全_r1_q7_3",
      "sug_表情包搞笑配文_r1_q7_4",
      "sug_表情包发给女朋友_r1_q7_5",
      "sug_表情包简笔画_r1_q7_6",
      "sug_表情包模板_r1_q7_7",
      "sug_表情包发给男朋友_r1_q7_8",
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      "sug_梗图素材_r1_q8_0",
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      "sug_梗图精神状态_r1_q8_2",
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      "sug_梗图双人_r1_q8_4",
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    "20": [
      "round_2",
      "step_sug_r2",
      "step_comb_r2",
      "step_search_r2",
      "step_next_round_r2"
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    "22": [
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      "q_双标表情包_r2_2",
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      "q_双标图片_r2_7",
      "q_表情包图片大全_r2_8",
      "q_梗图meme_r2_9",
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      "q_猫咪表情包_r2_12",
      "q_猫咪梗图_r2_13",
      "q_表情包梗图_r2_14",
      "q_反映人类双标_r2_15",
      "q_反映人类双标行为_r2_16",
      "q_人类双标行为_r2_17",
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      "q_人类行为_r2_21",
      "comb_如何反映_r2_0",
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      "comb_如何双标_r2_2",
      "comb_如何行为_r2_3",
      "comb_如何反映人类_r2_4",
      "comb_如何反映双标_r2_5",
      "comb_如何反映行为_r2_6",
      "comb_如何人类双标_r2_7",
      "comb_如何人类行为_r2_8",
      "comb_如何双标行为_r2_9",
      "comb_如何反映人类双标_r2_10",
      "comb_如何反映人类行为_r2_11",
      "comb_如何反映双标行为_r2_12",
      "comb_如何人类双标行为_r2_13",
      "comb_如何反映人类双标行为_r2_14",
      "comb_如何猫咪_r2_15",
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      "comb_如何梗图_r2_17",
      "comb_如何猫咪表情包_r2_18",
      "comb_如何猫咪梗图_r2_19",
      "comb_如何表情包梗图_r2_20",
      "comb_如何猫咪表情包梗图_r2_21",
      "comb_制作反映_r2_22",
      "comb_制作人类_r2_23",
      "comb_制作双标_r2_24",
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      "comb_制作人类行为_r2_30",
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      "comb_制作反映人类双标_r2_32",
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      "comb_制作人类双标行为_r2_35",
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      "comb_制作猫咪_r2_37",
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      "comb_制作猫咪梗图_r2_41",
      "comb_制作表情包梗图_r2_42",
      "comb_制作猫咪表情包梗图_r2_43",
      "comb_反映猫咪_r2_44",
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      "comb_人类猫咪表情包_r2_54",
      "comb_人类猫咪梗图_r2_55",
      "comb_人类表情包梗图_r2_56",
      "comb_人类猫咪表情包梗图_r2_57",
      "comb_双标猫咪_r2_58",
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      "comb_双标猫咪表情包梗图_r2_64",
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      "comb_行为猫咪梗图_r2_69",
      "comb_行为表情包梗图_r2_70",
      "comb_行为猫咪表情包梗图_r2_71",
      "comb_反映人类猫咪_r2_72",
      "comb_反映人类表情包_r2_73",
      "comb_反映人类梗图_r2_74",
      "comb_反映人类猫咪表情包_r2_75",
      "comb_反映人类猫咪梗图_r2_76",
      "comb_反映人类表情包梗图_r2_77",
      "comb_反映人类猫咪表情包梗图_r2_78",
      "comb_反映双标猫咪_r2_79",
      "comb_反映双标表情包_r2_80",
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      "comb_反映行为猫咪_r2_86",
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      "comb_反映行为猫咪梗图_r2_90",
      "comb_反映行为表情包梗图_r2_91",
      "comb_反映行为猫咪表情包梗图_r2_92",
      "comb_人类双标猫咪_r2_93",
      "comb_人类双标表情包_r2_94",
      "comb_人类双标梗图_r2_95",
      "comb_人类双标猫咪表情包_r2_96",
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      "comb_人类双标表情包梗图_r2_98",
      "comb_人类双标猫咪表情包梗图_r2_99",
      "comb_人类行为猫咪_r2_100",
      "comb_人类行为表情包_r2_101",
      "comb_人类行为梗图_r2_102",
      "comb_人类行为猫咪表情包_r2_103",
      "comb_人类行为猫咪梗图_r2_104",
      "comb_人类行为表情包梗图_r2_105",
      "comb_人类行为猫咪表情包梗图_r2_106",
      "comb_双标行为猫咪_r2_107",
      "comb_双标行为表情包_r2_108",
      "comb_双标行为梗图_r2_109",
      "comb_双标行为猫咪表情包_r2_110",
      "comb_双标行为猫咪梗图_r2_111",
      "comb_双标行为表情包梗图_r2_112",
      "comb_双标行为猫咪表情包梗图_r2_113",
      "comb_反映人类双标猫咪_r2_114",
      "comb_反映人类双标表情包_r2_115",
      "comb_反映人类双标梗图_r2_116",
      "comb_反映人类双标猫咪表情包_r2_117",
      "comb_反映人类双标猫咪梗图_r2_118",
      "comb_反映人类双标表情包梗图_r2_119",
      "comb_反映人类双标猫咪表情包梗图_r2_120",
      "comb_反映人类行为猫咪_r2_121",
      "comb_反映人类行为表情包_r2_122",
      "comb_反映人类行为梗图_r2_123",
      "comb_反映人类行为猫咪表情包_r2_124",
      "comb_反映人类行为猫咪梗图_r2_125",
      "comb_反映人类行为表情包梗图_r2_126",
      "comb_反映人类行为猫咪表情包梗图_r2_127",
      "comb_反映双标行为猫咪_r2_128",
      "comb_反映双标行为表情包_r2_129",
      "comb_反映双标行为梗图_r2_130",
      "comb_反映双标行为猫咪表情包_r2_131",
      "comb_反映双标行为猫咪梗图_r2_132",
      "comb_反映双标行为表情包梗图_r2_133",
      "comb_反映双标行为猫咪表情包梗图_r2_134",
      "comb_人类双标行为猫咪_r2_135",
      "comb_人类双标行为表情包_r2_136",
      "comb_人类双标行为梗图_r2_137",
      "comb_人类双标行为猫咪表情包_r2_138",
      "comb_人类双标行为猫咪梗图_r2_139",
      "comb_人类双标行为表情包梗图_r2_140",
      "comb_人类双标行为猫咪表情包梗图_r2_141",
      "comb_反映人类双标行为猫咪_r2_142",
      "comb_反映人类双标行为表情包_r2_143",
      "comb_反映人类双标行为梗图_r2_144",
      "comb_反映人类双标行为猫咪表情包_r2_145",
      "comb_反映人类双标行为猫咪梗图_r2_146",
      "comb_反映人类双标行为表情包梗图_r2_147",
      "comb_反映人类双标行为猫咪表情包梗图_r2_148",
      "search_制作表情包教程_r2_0",
      "search_怼双标的人表情包_r2_1",
      "search_可爱又双标的表情包_r2_2",
      "search_梗图描改教程_r2_3",
      "search_梗图meme原创_r2_4",
      "search_猫咪表情包梗图搞笑_r2_5",
      "search_猫咪表情包制作_r2_6",
      "next_round_制作猫咪表情包梗图_r2_0",
      "next_round_制作猫咪表情包_r2_1",
      "next_round_制作猫咪梗图_r2_2",
      "next_round_制作表情包梗图_r2_3",
      "next_round_制作表情包_r2_4",
      "next_round_制作反映人类双标行为_r2_5",
      "next_round_制作反映人类双标_r2_6",
      "next_round_制作人类双标_r2_7",
      "next_round_制作人类双标行为_r2_8",
      "next_round_制作反映双标_r2_9",
      "next_round_制作反映双标行为_r2_10",
      "next_round_制作双标行为_r2_11",
      "next_round_制作反映人类行为_r2_12",
      "next_round_反映人类双标猫咪表情包_r2_13",
      "next_round_反映双标猫咪梗图_r2_14",
      "next_round_如何猫咪表情包梗图_r2_15",
      "next_round_反映人类双标行为表情包梗图_r2_16",
      "next_round_如何猫咪表情包_r2_17",
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      "next_round_反映双标行为表情包梗图_r2_19",
      "next_round_反映行为猫咪梗图_r2_20",
      "next_round_如何表情包梗图_r2_21",
      "next_round_反映行为表情包梗图_r2_22",
      "next_round_如何反映人类双标行为_r2_23",
      "next_round_如何反映人类双标_r2_24",
      "next_round_如何反映双标_r2_25",
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      "next_round_如何反映人类行为_r2_27",
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      "next_round_猫咪梗图英文_r2_74",
      "next_round_梗图描改模板_r2_75",
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      "next_round_暗示双标的图片_r2_77",
      "next_round_meme梗图分享_r2_78",
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      "next_round_双标_r2_80",
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// 根据节点类型获取边框颜色
function getNodeTypeColor(type) {
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    'root': '#6b21a8',        // 紫色 - 根节点
    'round': '#7c3aed',       // 深紫 - Round节点
    'step': '#f59e0b',        // 橙色 - 步骤节点
    'seg': '#10b981',         // 绿色 - 分词
    'q': '#3b82f6',           // 蓝色 - Query
    'sug': '#06b6d4',         // 青色 - Sug建议词
    'seed': '#84cc16',        // 黄绿 - Seed
    'add_word': '#22c55e',    // 绿色 - 加词生成
    'search_word': '#8b5cf6', // 紫色 - 搜索词
    'post': '#ec4899',        // 粉色 - 帖子
    'filtered_sug': '#14b8a6',// 青绿 - 筛选的sug
    'next_q': '#2563eb',      // 深蓝 - 下轮查询
    'next_seed': '#65a30d',   // 深黄绿 - 下轮种子
    'search': '#8b5cf6',      // 深紫 - 搜索（兼容旧版）
    'operation': '#f59e0b',   // 橙色 - 操作节点（兼容旧版）
    'query': '#3b82f6',       // 蓝色 - 查询（兼容旧版）
    'note': '#ec4899',        // 粉色 - 帖子（兼容旧版）
  };
  return typeColors[type] || '#9ca3af';
}

// 查询节点组件 - 卡片样式
function QueryNode({ id, data, sourcePosition, targetPosition }) {
  // 所有节点默认展开
  const expanded = true;

  // 获取节点类型颜色
  const typeColor = getNodeTypeColor(data.nodeType || 'query');

  return (
    <div>
      <Handle
        type="target"
        position={targetPosition || Position.Left}
        style={{ background: typeColor, width: 8, height: 8 }}
      />
      <div
        style={{
          padding: '12px',
          borderRadius: '8px',
          border: data.isHighlighted ? `3px solid ${typeColor}` :
                  data.isCollapsed ? `2px solid ${typeColor}` :
                  data.isSelected === false ? '2px dashed #d1d5db' :
                  `2px solid ${typeColor}`,
          background: data.isHighlighted ? '#eef2ff' :
                      data.isSelected === false ? '#f9fafb' : 'white',
          minWidth: '200px',
          maxWidth: '280px',
          boxShadow: data.isHighlighted ? '0 0 0 4px rgba(102, 126, 234, 0.25), 0 4px 16px rgba(102, 126, 234, 0.4)' :
                     data.isCollapsed ? '0 4px 12px rgba(102, 126, 234, 0.15)' :
                     data.level === 0 ? '0 4px 12px rgba(139, 92, 246, 0.15)' : '0 2px 6px rgba(0, 0, 0, 0.06)',
          transition: 'all 0.3s ease',
          cursor: 'pointer',
          position: 'relative',
          opacity: data.isSelected === false ? 0.6 : 1,
        }}
      >
        {/* 折叠当前节点按钮 - 左边 */}
        <div
          style={{
            position: 'absolute',
            top: '6px',
            left: '6px',
            width: '20px',
            height: '20px',
            borderRadius: '50%',
            background: '#f59e0b',
            color: 'white',
            display: 'flex',
            alignItems: 'center',
            justifyContent: 'center',
            fontSize: '11px',
            fontWeight: 'bold',
            cursor: 'pointer',
            transition: 'all 0.2s ease',
            zIndex: 10,
          }}
          onClick={(e) => {
            e.stopPropagation();
            if (data.onHideSelf) {
              data.onHideSelf();
            }
          }}
          onMouseEnter={(e) => {
            e.currentTarget.style.background = '#d97706';
          }}
          onMouseLeave={(e) => {
            e.currentTarget.style.background = '#f59e0b';
          }}
          title="隐藏当前节点"
        >
          ×
        </div>

        {/* 聚焦按钮 - 右上角 */}
        <div
          style={{
            position: 'absolute',
            top: '6px',
            right: '6px',
            width: '20px',
            height: '20px',
            borderRadius: '50%',
            background: data.isFocused ? '#10b981' : '#e5e7eb',
            color: data.isFocused ? 'white' : '#6b7280',
            display: 'flex',
            alignItems: 'center',
            justifyContent: 'center',
            fontSize: '11px',
            fontWeight: 'bold',
            cursor: 'pointer',
            transition: 'all 0.2s ease',
            zIndex: 10,
          }}
          onClick={(e) => {
            e.stopPropagation();
            if (data.onFocus) {
              data.onFocus();
            }
          }}
          onMouseEnter={(e) => {
            if (!data.isFocused) {
              e.currentTarget.style.background = '#d1d5db';
            }
          }}
          onMouseLeave={(e) => {
            if (!data.isFocused) {
              e.currentTarget.style.background = '#e5e7eb';
            }
          }}
          title={data.isFocused ? '取消聚焦' : '聚焦到此节点'}
        >
          🎯
        </div>

        {/* 折叠/展开子节点按钮 - 右边第二个位置 */}
        {data.hasChildren && (
          <div
            style={{
              position: 'absolute',
              top: '6px',
              right: '30px',
              width: '20px',
              height: '20px',
              borderRadius: '50%',
              background: data.isCollapsed ? '#667eea' : '#e5e7eb',
              color: data.isCollapsed ? 'white' : '#6b7280',
              display: 'flex',
              alignItems: 'center',
              justifyContent: 'center',
              fontSize: '11px',
              fontWeight: 'bold',
              cursor: 'pointer',
              transition: 'all 0.2s ease',
              zIndex: 10,
            }}
            onClick={(e) => {
              e.stopPropagation();
              data.onToggleCollapse();
            }}
            title={data.isCollapsed ? '展开子节点' : '折叠子节点'}
          >
            {data.isCollapsed ? '+' : '−'}
          </div>
        )}

        {/* 卡片内容 */}
        <div>
          {/* 标题行 */}
          <div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'flex-start', marginBottom: '8px', paddingLeft: '24px', paddingRight: data.hasChildren ? '54px' : '28px' }}>
            <div style={{ flex: 1 }}>
              <div style={{ display: 'flex', alignItems: 'center', gap: '4px', marginBottom: '3px' }}>
                <div style={{
                  fontSize: '13px',
                  fontWeight: data.level === 0 ? '700' : '600',
                  color: data.level === 0 ? '#6b21a8' : '#1f2937',
                  lineHeight: '1.3',
                  flex: 1,
                }}>
                  {data.title}
                </div>
                {data.isSelected === false && (
                  <div style={{
                    fontSize: '9px',
                    padding: '1px 4px',
                    borderRadius: '3px',
                    background: '#fee2e2',
                    color: '#991b1b',
                    fontWeight: '500',
                    flexShrink: 0,
                  }}>
                    未选中
                  </div>
                )}
              </div>
            </div>
          </div>

        {/* 展开的详细信息 - 始终显示 */}
        <div style={{ fontSize: '11px', lineHeight: 1.4 }}>
            <div style={{ display: 'flex', gap: '4px', marginBottom: '6px', flexWrap: 'wrap' }}>
              <span style={{
                display: 'inline-block',
                padding: '1px 6px',
                borderRadius: '10px',
                background: '#eff6ff',
                color: '#3b82f6',
                fontSize: '10px',
                fontWeight: '500',
              }}>
                Lv.{data.level}
              </span>
              <span style={{
                display: 'inline-block',
                padding: '1px 6px',
                borderRadius: '10px',
                background: '#f0fdf4',
                color: '#16a34a',
                fontSize: '10px',
                fontWeight: '500',
              }}>
                {data.score}
              </span>
              {data.strategy && data.strategy !== 'root' && (
                <span style={{
                  display: 'inline-block',
                  padding: '1px 6px',
                  borderRadius: '10px',
                  background: '#fef3c7',
                  color: '#92400e',
                  fontSize: '10px',
                  fontWeight: '500',
                }}>
                  {data.strategy}
                </span>
              )}
              {(data.typeLabel || data.type_label) && (
                <span style={{
                  display: 'inline-block',
                  padding: '1px 6px',
                  borderRadius: '10px',
                  background: '#fce7f3',
                  color: '#9f1239',
                  fontSize: '10px',
                  fontWeight: '500',
                }}>
                  {data.typeLabel || data.type_label}
                </span>
              )}
            {data.is_suggestion && data.suggestion_label && (
              <span style={{
                display: 'inline-block',
                padding: '1px 6px',
                borderRadius: '10px',
                background: '#ede9fe',
                color: '#6d28d9',
                fontSize: '10px',
                fontWeight: '600',
              }}>
                {data.suggestion_label}
              </span>
            )}
            </div>

            {data.parent && (
              <div style={{ color: '#6b7280', fontSize: '10px', marginTop: '4px', paddingTop: '4px', borderTop: '1px solid #f3f4f6' }}>
                <strong>Parent:</strong> {data.parent}
              </div>
            )}
            {data.nodeType === 'domain_combination' && Array.isArray(data.source_word_details) && data.source_word_details.length > 0 && (
              <div style={{
                marginTop: '6px',
                paddingTop: '6px',
                borderTop: '1px solid #f3f4f6',
                fontSize: '10px',
                color: '#6b7280',
                lineHeight: '1.5',
              }}>
                <strong style={{ color: '#4b5563' }}>来源词得分:</strong>
                <div style={{ marginTop: '4px', display: 'flex', flexDirection: 'column', gap: '4px' }}>
                  {data.source_word_details.map((detail, idx) => {
                    const words = (detail.words || []).map((w) => {
                      const numericScore = typeof w.score === 'number' ? w.score : parseFloat(w.score || '0');
                      const formattedScore = Number.isFinite(numericScore) ? numericScore.toFixed(2) : '0.00';
                      return w.text + ' (' + formattedScore + ')';
                    }).join(' + ');
                    return (
                      <div key={idx} style={{ display: 'flex', flexWrap: 'wrap', gap: '4px', alignItems: 'center' }}>
                        <span style={{ color: '#2563eb' }}>{words}</span>
                      </div>
                    );
                  })}
                </div>
                <div style={{ marginTop: '4px', fontWeight: '500', color: data.is_above_sources ? '#16a34a' : '#dc2626' }}>
                  {data.is_above_sources ? '✅ 组合得分高于所有来源词' : '⚠️ 组合得分未超过全部来源词'}
                </div>
              </div>
            )}
            {data.selectedWord && (
              <div style={{
                marginTop: '6px',
                paddingTop: '6px',
                borderTop: '1px solid #f3f4f6',
                fontSize: '10px',
                color: '#6b7280',
                lineHeight: '1.5',
              }}>
                <strong style={{ color: '#4b5563' }}>选择词:</strong>
                <span style={{ marginLeft: '4px', color: '#3b82f6', fontWeight: '500' }}>{data.selectedWord}</span>
                {data.seed_score !== undefined && (
                  <div style={{ marginTop: '4px' }}>
                    <strong style={{ color: '#4b5563' }}>种子得分:</strong>
                    <span style={{ marginLeft: '4px', color: '#16a34a', fontWeight: '500' }}>
                      {typeof data.seed_score === 'number' ? data.seed_score.toFixed(2) : data.seed_score}
                    </span>
                  </div>
                )}
              </div>
            )}
            {data.evaluationReason && (
              <div style={{
                marginTop: '6px',
                paddingTop: '6px',
                borderTop: '1px solid #f3f4f6',
                fontSize: '10px',
                color: '#6b7280',
                lineHeight: '1.5',
              }}>
                <strong style={{ color: '#4b5563' }}>评估:</strong>
                <div style={{ marginTop: '2px' }}>{data.evaluationReason}</div>
              </div>
            )}
            {data.occurrences && data.occurrences.length > 1 && (
              <div style={{
                marginTop: '6px',
                paddingTop: '6px',
                borderTop: '1px solid #f3f4f6',
                fontSize: '10px',
                color: '#6b7280',
              }}>
                <strong style={{ color: '#4b5563' }}>演化历史 ({data.occurrences.length}次):</strong>
                <div style={{ marginTop: '4px' }}>
                  {data.occurrences.map((occ, idx) => (
                    <div key={idx} style={{ marginTop: '2px', paddingLeft: '8px' }}>
                      <span style={{ color: '#3b82f6', fontWeight: '500' }}>R{occ.round}</span>
                      {' · '}
                      <span>{occ.strategy}</span>
                      {occ.score !== undefined && (
                        <span style={{ color: '#16a34a', marginLeft: '4px' }}>
                          ({typeof occ.score === 'number' ? occ.score.toFixed(2) : occ.score})
                        </span>
                      )}
                    </div>
                  ))}
                </div>
              </div>
            )}
            {data.hasSearchResults && (
              <div style={{
                marginTop: '6px',
                paddingTop: '6px',
                borderTop: '1px solid #f3f4f6',
                fontSize: '10px',
                background: '#fef3c7',
                padding: '4px 6px',
                borderRadius: '4px',
                color: '#92400e',
                fontWeight: '500',
              }}>
                🔍 找到 {data.postCount} 个帖子
              </div>
            )}
          </div>
        </div>
      </div>
      <Handle
        type="source"
        position={sourcePosition || Position.Right}
        style={{ background: '#667eea', width: 8, height: 8 }}
      />
    </div>
  );
}

// 笔记节点组件 - 卡片样式，带轮播图
function NoteNode({ id, data, sourcePosition, targetPosition }) {
  const [currentImageIndex, setCurrentImageIndex] = useState(0);
  const expanded = true;
  const hasImages = data.imageList && data.imageList.length > 0;

  const nextImage = (e) => {
    e.stopPropagation();
    if (hasImages) {
      setCurrentImageIndex((prev) => (prev + 1) % data.imageList.length);
    }
  };

  const prevImage = (e) => {
    e.stopPropagation();
    if (hasImages) {
      setCurrentImageIndex((prev) => (prev - 1 + data.imageList.length) % data.imageList.length);
    }
  };

  return (
    <div>
      <Handle
        type="target"
        position={targetPosition || Position.Left}
        style={{ background: '#ec4899', width: 8, height: 8 }}
      />
      <div
        style={{
          padding: '14px',
          borderRadius: '20px',
          border: data.isHighlighted ? '3px solid #ec4899' : '2px solid #fce7f3',
          background: data.isHighlighted ? '#eef2ff' : 'white',
          minWidth: '220px',
          maxWidth: '300px',
          boxShadow: data.isHighlighted ? '0 0 0 4px rgba(236, 72, 153, 0.25), 0 4px 16px rgba(236, 72, 153, 0.4)' : '0 4px 12px rgba(236, 72, 153, 0.15)',
          transition: 'all 0.3s ease',
          cursor: 'pointer',
        }}
      >
        {/* 笔记标题 */}
        <div style={{ display: 'flex', alignItems: 'flex-start', marginBottom: '8px' }}>
          <div style={{ flex: 1 }}>
            <div style={{
              fontSize: '13px',
              fontWeight: '600',
              color: '#831843',
              lineHeight: '1.4',
              marginBottom: '4px',
            }}>
              {data.title}
            </div>
          </div>
        </div>

        {/* 评估信息区域 */}
        {(data.is_knowledge !== undefined && data.is_knowledge !== null || data.post_relevance_score !== undefined && data.post_relevance_score !== null) && (
          <div style={{
            marginBottom: '10px',
            paddingBottom: '8px',
            borderBottom: '1px solid #fce7f3',
          }}>
            {/* 知识判定标签 */}
            {(data.is_knowledge !== undefined && data.is_knowledge !== null) && (
              <div style={{ marginBottom: '8px' }}>
                <span style={{
                  display: 'inline-block',
                  padding: '3px 10px',
                  borderRadius: '12px',
                  fontSize: '11px',
                  fontWeight: '600',
                  background: data.is_knowledge ? '#dcfce7' : '#fee2e2',
                  color: data.is_knowledge ? '#166534' : '#991b1b',
                }}>
                  {data.is_knowledge ? '✓ 知识内容' : '✗ 非知识'}
                </span>
                {data.knowledge_reason && (
                  <div style={{
                    marginTop: '4px',
                    fontSize: '10px',
                    color: '#9f1239',
                    lineHeight: '1.4',
                  }}>
                    {data.knowledge_reason}
                  </div>
                )}
              </div>
            )}

            {/* 相关性得分 */}
            {(data.post_relevance_score !== undefined && data.post_relevance_score !== null) && (
              <div>
                <div style={{
                  display: 'flex',
                  alignItems: 'center',
                  gap: '6px',
                  marginBottom: '4px',
                }}>
                  <span style={{
                    fontSize: '11px',
                    fontWeight: '600',
                    color: '#9f1239',
                  }}>
                    相关性: {(data.post_relevance_score * 100).toFixed(0)}%
                  </span>
                  {data.relevance_level && (
                    <span style={{
                      padding: '2px 8px',
                      borderRadius: '10px',
                      fontSize: '10px',
                      fontWeight: '600',
                      background:
                        data.relevance_level === '高度相关' ? '#dcfce7' :
                        data.relevance_level === '中度相关' ? '#fef3c7' : '#fee2e2',
                      color:
                        data.relevance_level === '高度相关' ? '#166534' :
                        data.relevance_level === '中度相关' ? '#854d0e' : '#991b1b',
                    }}>
                      {data.relevance_level}
                    </span>
                  )}
                </div>
                {data.relevance_reason && (
                  <div style={{
                    fontSize: '10px',
                    color: '#9f1239',
                    lineHeight: '1.4',
                  }}>
                    {data.relevance_reason}
                  </div>
                )}
              </div>
            )}
          </div>
        )}

        {/* 轮播图 */}
        {hasImages && (
          <div style={{
            position: 'relative',
            marginBottom: '8px',
            borderRadius: '12px',
            overflow: 'hidden',
          }}>
            <img
              src={data.imageList[currentImageIndex].image_url}
              alt={`Image ${currentImageIndex + 1}`}
              style={{
                width: '100%',
                height: '160px',
                objectFit: 'cover',
                display: 'block',
              }}
              onError={(e) => {
                e.target.style.display = 'none';
              }}
            />
            {data.imageList.length > 1 && (
              <>
                {/* 左右切换按钮 */}
                <button
                  onClick={prevImage}
                  style={{
                    position: 'absolute',
                    left: '4px',
                    top: '50%',
                    transform: 'translateY(-50%)',
                    background: 'rgba(0, 0, 0, 0.5)',
                    color: 'white',
                    border: 'none',
                    borderRadius: '50%',
                    width: '24px',
                    height: '24px',
                    cursor: 'pointer',
                    display: 'flex',
                    alignItems: 'center',
                    justifyContent: 'center',
                    fontSize: '14px',
                  }}
                >
                  ‹
                </button>
                <button
                  onClick={nextImage}
                  style={{
                    position: 'absolute',
                    right: '4px',
                    top: '50%',
                    transform: 'translateY(-50%)',
                    background: 'rgba(0, 0, 0, 0.5)',
                    color: 'white',
                    border: 'none',
                    borderRadius: '50%',
                    width: '24px',
                    height: '24px',
                    cursor: 'pointer',
                    display: 'flex',
                    alignItems: 'center',
                    justifyContent: 'center',
                    fontSize: '14px',
                  }}
                >
                  ›
                </button>
                {/* 图片计数 */}
                <div style={{
                  position: 'absolute',
                  bottom: '4px',
                  right: '4px',
                  background: 'rgba(0, 0, 0, 0.6)',
                  color: 'white',
                  padding: '2px 6px',
                  borderRadius: '10px',
                  fontSize: '10px',
                }}>
                  {currentImageIndex + 1}/{data.imageList.length}
                </div>
              </>
            )}
          </div>
        )}

        {/* 互动数据 */}
        {data.interact_info && (
          <div style={{
            display: 'flex',
            gap: '8px',
            marginBottom: '8px',
            flexWrap: 'wrap',
            fontSize: '11px',
            color: '#9f1239',
          }}>
            {data.interact_info.liked_count > 0 && (
              <span style={{ display: 'flex', alignItems: 'center', gap: '2px' }}>
                ❤️ {data.interact_info.liked_count}
              </span>
            )}
            {data.interact_info.collected_count > 0 && (
              <span style={{ display: 'flex', alignItems: 'center', gap: '2px' }}>
                ⭐ {data.interact_info.collected_count}
              </span>
            )}
            {data.interact_info.comment_count > 0 && (
              <span style={{ display: 'flex', alignItems: 'center', gap: '2px' }}>
                💬 {data.interact_info.comment_count}
              </span>
            )}
            {data.interact_info.shared_count > 0 && (
              <span style={{ display: 'flex', alignItems: 'center', gap: '2px' }}>
                🔗 {data.interact_info.shared_count}
              </span>
            )}
          </div>
        )}

        {/* 被哪些query找到 */}
        {data.foundByQueries && data.foundByQueries.length > 0 && (
          <div style={{
            marginBottom: '8px',
            padding: '6px 8px',
            background: '#f0fdf4',
            borderRadius: '6px',
            fontSize: '10px',
          }}>
            <strong style={{ color: '#16a34a' }}>🔍 被找到:</strong>
            <div style={{ marginTop: '4px', display: 'flex', flexWrap: 'wrap', gap: '4px' }}>
              {data.foundByQueries.map((query, idx) => (
                <span key={idx} style={{
                  display: 'inline-block',
                  padding: '2px 6px',
                  background: '#dcfce7',
                  color: '#166534',
                  borderRadius: '4px',
                  fontSize: '9px',
                }}>
                  {query}
                </span>
              ))}
            </div>
            {data.foundInRounds && data.foundInRounds.length > 0 && (
              <div style={{ marginTop: '4px', color: '#6b7280' }}>
                出现在: Round {data.foundInRounds.join(', ')}
              </div>
            )}
          </div>
        )}

        {/* 标签 */}
        {(data.matchLevel || data.score) && (
          <div style={{ display: 'flex', gap: '6px', marginBottom: '8px', flexWrap: 'wrap' }}>
            {data.matchLevel && (
              <span style={{
                display: 'inline-block',
                padding: '2px 8px',
                borderRadius: '12px',
                background: '#fff1f2',
                color: '#be123c',
                fontSize: '10px',
                fontWeight: '500',
              }}>
                {data.matchLevel}
              </span>
            )}
            {data.score && (
              <span style={{
                display: 'inline-block',
                padding: '2px 8px',
                borderRadius: '12px',
                background: '#fff7ed',
                color: '#c2410c',
                fontSize: '10px',
                fontWeight: '500',
              }}>
                Score: {data.score}
              </span>
            )}
          </div>
        )}

        {/* 描述 */}
        {expanded && data.description && (
          <div style={{
            fontSize: '11px',
            color: '#9f1239',
            lineHeight: '1.5',
            paddingTop: '8px',
            borderTop: '1px solid #fbcfe8',
          }}>
            {data.description}
          </div>
        )}

        {/* 评估理由 */}
        {expanded && data.evaluationReason && (
          <div style={{
            fontSize: '10px',
            color: '#831843',
            lineHeight: '1.5',
            paddingTop: '8px',
            marginTop: '8px',
            borderTop: '1px solid #fbcfe8',
          }}>
            <strong style={{ color: '#9f1239' }}>评估:</strong>
            <div style={{ marginTop: '2px' }}>{data.evaluationReason}</div>
          </div>
        )}
      </div>
      <Handle
        type="source"
        position={sourcePosition || Position.Right}
        style={{ background: '#ec4899', width: 8, height: 8 }}
      />
    </div>
  );
}

// AnalysisNode 组件：展示AI分析（左侧OCR文字，右侧缩略图+描述）
function AnalysisNode({ data }) {
  const nodeStyle = {
    background: '#fffbeb',
    border: '2px solid #fbbf24',
    borderRadius: '8px',
    padding: '12px',
    minWidth: '700px',
    maxWidth: '900px',
    fontSize: '12px',
    boxShadow: '0 4px 6px rgba(0,0,0,0.1)',
  };

  return (
    <div style={nodeStyle}>
      <Handle
        type="target"
        position={Position.Left}
        style={{ background: '#fbbf24', width: 8, height: 8 }}
      />

      {/* 标题 */}
      <div style={{
        fontSize: '14px',
        fontWeight: 'bold',
        marginBottom: '8px',
        color: '#92400e',
      }}>
        🖼️ {data.query}
      </div>

      {/* 评分和互动数据 */}
      <div style={{
        display: 'flex',
        justifyContent: 'space-between',
        marginBottom: '8px',
        padding: '6px',
        background: '#fef3c7',
        borderRadius: '4px',
      }}>
        <div style={{ fontSize: '11px', fontWeight: 'bold' }}>
          Score: {data.interact_info?.relevance_score || 0}
        </div>
        <div style={{ display: 'flex', gap: '12px', fontSize: '11px' }}>
          {data.interact_info?.liked_count > 0 && (
            <span>❤️ {data.interact_info.liked_count}</span>
          )}
          {data.interact_info?.collected_count > 0 && (
            <span>⭐ {data.interact_info.collected_count}</span>
          )}
          {data.interact_info?.comment_count > 0 && (
            <span>💬 {data.interact_info.comment_count}</span>
          )}
        </div>
      </div>

      {/* 完整正文内容 */}
      {data.body_text && (
        <div style={{
          padding: '8px',
          background: 'white',
          borderRadius: '4px',
          marginBottom: '12px',
          fontSize: '11px',
          lineHeight: '1.5',
          border: '1px solid #fbbf24',
          whiteSpace: 'pre-wrap',
          wordBreak: 'break-word',
        }}>
          {data.body_text}
        </div>
      )}

      {/* AI分析 - 左右分栏 */}
      {data.extraction && data.extraction.images && (
        <div style={{
          display: 'flex',
          flexDirection: 'column',
          gap: '12px',
        }}>
          {data.extraction.images.map((img, idx) => (
            <div
              key={idx}
              style={{
                display: 'flex',
                flexDirection: 'row',
                gap: '16px',
                padding: '10px',
                background: 'white',
                borderRadius: '4px',
                border: '1px solid #d97706',
                alignItems: 'flex-start',
              }}
            >
              {/* 左侧：OCR提取文字 */}
              <div style={{
                flex: '1',  // 1/3宽度
                minWidth: '0',
              }}>
                <div style={{
                  fontSize: '11px',
                  fontWeight: 'bold',
                  color: '#92400e',
                  marginBottom: '6px',
                }}>
                  📝 图片 {idx + 1}/{data.extraction.images.length}
                </div>

                {img.extract_text && (
                  <div style={{
                    fontSize: '11px',
                    color: '#1f2937',
                    lineHeight: '1.6',
                    padding: '8px',
                    background: '#fef9e7',
                    borderRadius: '3px',
                    borderLeft: '3px solid #f39c12',
                    wordBreak: 'break-word',
                  }}>
                    <div style={{
                      fontSize: '10px',
                      fontWeight: 'bold',
                      color: '#d97706',
                      marginBottom: '4px',
                    }}>
                      【提取文字】
                    </div>
                    {img.extract_text}
                  </div>
                )}
              </div>

              {/* 右侧：缩略图 + 描述 */}
              <div style={{
                flex: '2',  // 2/3宽度
                display: 'flex',
                flexDirection: 'column',
                gap: '8px',
                minWidth: '200px',
              }}>
                {/* 缩略图 */}
                {data.image_list && data.image_list[idx] && (
                  <img
                    src={(data.image_list[idx].image_url || data.image_list[idx])}
                    alt={'图片' + (idx + 1)}
                    style={{
                      width: '100%',
                      height: 'auto',
                      maxHeight: '180px',
                      objectFit: 'contain',
                      borderRadius: '4px',
                      border: '1px solid #d97706',
                      cursor: 'pointer',
                    }}
                    onError={(e) => {
                      e.target.style.display = 'none';
                    }}
                  />
                )}

                {/* 描述文字（完整展示） */}
                {img.description && (
                  <div
                    style={{
                      fontSize: '10px',
                      color: '#78350f',
                      lineHeight: '1.5',
                      wordBreak: 'break-word',
                      padding: '8px',
                      background: '#fef9e7',
                      borderRadius: '3px',
                      border: '1px solid #f39c12',
                    }}
                  >
                    <div style={{
                      fontSize: '9px',
                      fontWeight: 'bold',
                      color: '#d97706',
                      marginBottom: '4px',
                    }}>
                      【图片描述】
                    </div>
                    {img.description}
                  </div>
                )}
              </div>
            </div>
          ))}
        </div>
      )}

      {/* 查看原帖链接 */}
      {data.note_url && (
        <div style={{ marginTop: '8px', fontSize: '10px' }}>
          <a
            href={data.note_url}
            target="_blank"
            rel="noopener noreferrer"
            style={{ color: '#92400e', textDecoration: 'underline' }}
          >
            🔗 查看原帖
          </a>
        </div>
      )}

      <Handle
        type="source"
        position={Position.Right}
        style={{ background: '#fbbf24', width: 8, height: 8 }}
      />
    </div>
  );
}

const nodeTypes = {
  query: QueryNode,
  note: NoteNode,
  post: NoteNode,  // 帖子节点使用 NoteNode 组件渲染
  analysis: AnalysisNode,
};

// 根据 score 获取颜色
function getScoreColor(score) {
  if (score >= 0.7) return '#10b981'; // 绿色 - 高分
  if (score >= 0.4) return '#f59e0b'; // 橙色 - 中分
  return '#ef4444'; // 红色 - 低分
}

// 截断文本，保留头尾，中间显示省略号
function truncateMiddle(text, maxLength = 20) {
  if (!text || text.length <= maxLength) return text;
  const headLength = Math.ceil(maxLength * 0.4);
  const tailLength = Math.floor(maxLength * 0.4);
  const head = text.substring(0, headLength);
  const tail = text.substring(text.length - tailLength);
  return `${head}...${tail}`;
}

// 根据策略获取颜色
// 智能提取主要策略的辅助函数
function getPrimaryStrategy(nodeData) {
  // 优先级1: 使用 primaryStrategy 字段
  if (nodeData.primaryStrategy) {
    return nodeData.primaryStrategy;
  }

  // 优先级2: 从 occurrences 数组中获取最新的策略
  if (nodeData.occurrences && Array.isArray(nodeData.occurrences) && nodeData.occurrences.length > 0) {
    const latestOccurrence = nodeData.occurrences[nodeData.occurrences.length - 1];
    if (latestOccurrence && latestOccurrence.strategy) {
      return latestOccurrence.strategy;
    }
  }

  // 优先级3: 拆分组合策略字符串，取第一个
  if (nodeData.strategy && typeof nodeData.strategy === 'string') {
    const strategies = nodeData.strategy.split(' + ');
    if (strategies.length > 0 && strategies[0]) {
      return strategies[0].trim();
    }
  }

  // 默认返回原始strategy或未知
  return nodeData.strategy || '未知';
}

function getStrategyColor(strategy) {
  const strategyColors = {
    '初始分词': '#10b981',
    '调用sug': '#06b6d4',
    '同义改写': '#f59e0b',
    '加词': '#3b82f6',
    '抽象改写': '#8b5cf6',
    '基于部分匹配改进': '#ec4899',
    '结果分支-抽象改写': '#a855f7',
    '结果分支-同义改写': '#fb923c',
    // v6.1.2.8 新增策略
    '原始问题': '#6b21a8',
    '来自分词': '#10b981',
    '加词生成': '#ef4444',
    '建议词': '#06b6d4',
    '执行搜索': '#8b5cf6',
    // 添加简化版本的策略映射
    '分词': '#10b981',
    '推荐词': '#06b6d4',
  };
  return strategyColors[strategy] || '#9ca3af';
}

// 树节点组件
function TreeNode({ node, level, children, isCollapsed, onToggle, isSelected, onSelect }) {
  const hasChildren = children && children.length > 0;
  const score = node.data.score ? parseFloat(node.data.score) : 0;
  const strategy = getPrimaryStrategy(node.data);  // 使用智能提取函数
  const strategyColor = getStrategyColor(strategy);
  const nodeActualType = node.data.nodeType || node.type; // 获取实际节点类型
  const isDomainCombination = nodeActualType === 'domain_combination';

  let sourceSummary = '';
  if (isDomainCombination && Array.isArray(node.data.source_word_details) && node.data.source_word_details.length > 0) {
    const summaryParts = [];
    node.data.source_word_details.forEach((detail) => {
      const words = Array.isArray(detail.words) ? detail.words : [];
      const wordTexts = [];
      words.forEach((w) => {
        const numericScore = typeof w.score === 'number' ? w.score : parseFloat(w.score || '0');
        const formattedScore = Number.isFinite(numericScore) ? numericScore.toFixed(2) : '0.00';
        wordTexts.push(w.text + ' (' + formattedScore + ')');
      });
      if (wordTexts.length > 0) {
        const segmentLabel = detail.segment_type ? '[' + detail.segment_type + '] ' : '';
        summaryParts.push(segmentLabel + wordTexts.join(' + '));
      }
    });
    sourceSummary = summaryParts.join(' | ');
  }

  // 计算字体颜色：根据分数提升幅度判断
  let fontColor = '#374151'; // 默认颜色
  if (node.type === 'note') {
    fontColor = node.data.matchLevel === 'unsatisfied' ? '#ef4444' : '#374151';
  } else if (node.data.seed_score !== undefined) {
    const parentScore = parseFloat(node.data.seed_score);
    const gain = score - parentScore;
    fontColor = gain >= 0.05 ? '#16a34a' : '#ef4444';
  } else if (node.data.isSelected === false) {
    fontColor = '#ef4444';
  }

  return (
    <div style={{ marginLeft: level * 12 + 'px', marginBottom: '8px' }}>
      <div
        style={{
          padding: '6px 8px',
          borderRadius: '4px',
          cursor: 'pointer',
          background: 'transparent',
          border: isSelected ? '1px solid #3b82f6' : '1px solid transparent',
          display: 'flex',
          alignItems: 'center',
          gap: '6px',
          transition: 'all 0.2s ease',
          position: 'relative',
          overflow: 'visible',
        }}
        onMouseEnter={(e) => {
          if (!isSelected) e.currentTarget.style.background = '#f9fafb';
        }}
        onMouseLeave={(e) => {
          if (!isSelected) e.currentTarget.style.background = 'transparent';
        }}
      >
        {/* 策略类型竖线 */}
        <div style={{
          width: '3px',
          height: '20px',
          background: strategyColor,
          borderRadius: '2px',
          flexShrink: 0,
          position: 'relative',
          zIndex: 1,
        }} />

        {hasChildren && (
          <span
            style={{
              fontSize: '10px',
              color: '#6b7280',
              cursor: 'pointer',
              width: '16px',
              textAlign: 'center',
              position: 'relative',
              zIndex: 1,
            }}
            onClick={(e) => {
              e.stopPropagation();
              onToggle();
            }}
          >
            {isCollapsed ? '▶' : '▼'}
          </span>
        )}
        {!hasChildren && <span style={{ width: '16px', position: 'relative', zIndex: 1 }}></span>}

        <div
          style={{
            flex: 1,
            fontSize: '12px',
            color: '#374151',
            position: 'relative',
            zIndex: 1,
            minWidth: 0,
            display: 'flex',
            flexDirection: 'column',
            gap: '4px',
          }}
          onClick={onSelect}
        >
          <div style={{
            display: 'flex',
            alignItems: 'center',
            gap: '8px',
          }}>
            {/* 文本标题 - 左侧 */}
            <div style={{
              fontWeight: level === 0 ? '600' : '400',
              flex: 1,
              minWidth: 0,
              color: node.data.scoreColor || fontColor,
              overflow: 'hidden',
              textOverflow: 'ellipsis',
              whiteSpace: 'nowrap',
            }}
            title={node.data.title || node.id}
            >
              {node.data.title || node.id}
            </div>

            {/* 域标识 - 右侧，挨着分数，优先显示域类型，否则显示域索引或域字符串，但domain_combination节点不显示 */}
            {(node.data.domain_type || node.data.domains_str || (node.data.domain_index !== null && node.data.domain_index !== undefined)) && nodeActualType !== 'domain_combination' && (
              <span style={{
                fontSize: '12px',
                color: '#fff',
                background: '#6366f1',
                padding: '2px 5px',
                borderRadius: '3px',
                flexShrink: 0,
                fontWeight: '600',
                marginLeft: '4px',
              }}
              title={
                node.data.domain_type ? '域: ' + node.data.domain_type + ' (D' + node.data.domain_index + ')' :
                node.data.domains_str ? '域: ' + node.data.domains_str :
                '域 D' + node.data.domain_index
              }
              >
                {node.data.domain_type || node.data.domains_str || ('D' + node.data.domain_index)}
              </span>
            )}

            {node.data.is_suggestion && node.data.suggestion_label && (
              <span style={{
                fontSize: '12px',
                color: '#fff',
                background: '#8b5cf6',
                padding: '2px 5px',
                borderRadius: '3px',
                flexShrink: 0,
                fontWeight: '600',
              }}
              >
                {node.data.suggestion_label}
              </span>
            )}

            {/* 类型标签 - 显示在右侧靠近分数，蓝色背景 */}
            {node.data.type_label && (
              <span style={{
                fontSize: '12px',
                color: '#fff',
                background: '#6366f1',
                padding: '2px 5px',
                borderRadius: '3px',
                flexShrink: 0,
                fontWeight: '600',
              }}
              title={'类型: ' + node.data.type_label}
              >
                {node.data.type_label}
              </span>
            )}

            {/* 分数显示 - 步骤和轮次节点不显示分数 */}
            {nodeActualType !== 'step' && nodeActualType !== 'round' && (
              <span style={{
                fontSize: '11px',
                color: '#6b7280',
                fontWeight: '500',
                flexShrink: 0,
                minWidth: '35px',
                textAlign: 'right',
              }}>
                {score.toFixed(2)}
              </span>
            )}
          </div>

          {/* 域组合的来源词得分（树状视图，右对齐） */}
          {isDomainCombination && sourceSummary && (
            <div style={{
              fontSize: '10px',
              color: '#2563eb',
              lineHeight: '1.4',
              display: 'flex',
              flexDirection: 'column',
              alignItems: 'flex-end',
              gap: '2px',
              textAlign: 'right',
            }}>
              {node.data.source_word_details.map((detail, idx) => {
                const words = Array.isArray(detail.words) ? detail.words : [];
                const summary = words.map((w) => {
                  const numericScore = typeof w.score === 'number' ? w.score : parseFloat(w.score || '0');
                  const formattedScore = Number.isFinite(numericScore) ? numericScore.toFixed(2) : '0.00';
                  return w.text + ' (' + formattedScore + ')';
                }).join(' + ');
                return (
                  <span key={idx} title={summary}>
                    {summary}
                  </span>
                );
              })}
            </div>
          )}

          {/* 分数下划线 - 步骤和轮次节点不显示 */}
          {nodeActualType !== 'step' && nodeActualType !== 'round' && (
            <div style={{
              width: (score * 100) + '%',
              height: '2px',
              background: getScoreColor(score),
              borderRadius: '1px',
            }} />
          )}
        </div>
      </div>

      {hasChildren && !isCollapsed && (
        <div>
          {children}
        </div>
      )}
    </div>
  );
}

// 使用 dagre 自动布局
function getLayoutedElements(nodes, edges, direction = 'LR') {
  console.log('🎯 Starting layout with dagre...');
  console.log('Input:', nodes.length, 'nodes,', edges.length, 'edges');

  // 检查 dagre 是否加载
  if (typeof window === 'undefined' || typeof window.dagre === 'undefined') {
    console.warn('⚠️ Dagre not loaded, using fallback layout');
    // 降级到简单布局
    const levelGroups = {};
    nodes.forEach(node => {
      const level = node.data.level || 0;
      if (!levelGroups[level]) levelGroups[level] = [];
      levelGroups[level].push(node);
    });

    Object.entries(levelGroups).forEach(([level, nodeList]) => {
      const x = parseInt(level) * 480;
      nodeList.forEach((node, index) => {
        node.position = { x, y: index * 260 };
        node.targetPosition = 'left';
        node.sourcePosition = 'right';
      });
    });

    return { nodes, edges };
  }

  try {
    const dagreGraph = new window.dagre.graphlib.Graph();
    dagreGraph.setDefaultEdgeLabel(() => ({}));

    const isHorizontal = direction === 'LR';
    dagreGraph.setGraph({
      rankdir: direction,
      nodesep: 180,   // 垂直间距 - 增加以避免节点重叠
      ranksep: 360,  // 水平间距 - 增加以容纳更宽的节点
    });

    // 添加节点 - 根据节点类型设置不同的尺寸
    nodes.forEach((node) => {
      let nodeWidth = 320;
      let nodeHeight = 220;

      // note 节点有轮播图，需要更大的空间
      if (node.type === 'note') {
        nodeWidth = 360;
        nodeHeight = 380;  // 增加高度以容纳轮播图
      }
      // analysis 节点内容很多，需要更大的空间
      else if (node.type === 'analysis') {
        nodeWidth = 900;   // 宽度足够容纳左右分栏
        nodeHeight = 600;  // 高度足够容纳多张图片
      }

      dagreGraph.setNode(node.id, { width: nodeWidth, height: nodeHeight });
    });

    // 添加边
    edges.forEach((edge) => {
      dagreGraph.setEdge(edge.source, edge.target);
    });

    // 计算布局
    window.dagre.layout(dagreGraph);
    console.log('✅ Dagre layout completed');

    // 更新节点位置和 handle 位置
    nodes.forEach((node) => {
      const nodeWithPosition = dagreGraph.node(node.id);

      if (!nodeWithPosition) {
        console.warn('Node position not found for:', node.id);
        return;
      }

      node.targetPosition = isHorizontal ? 'left' : 'top';
      node.sourcePosition = isHorizontal ? 'right' : 'bottom';

      // 根据节点类型获取尺寸
      let nodeWidth = 320;
      let nodeHeight = 220;
      if (node.type === 'note') {
        nodeWidth = 360;
        nodeHeight = 380;
      }

      // 将 dagre 的中心点位置转换为 React Flow 的左上角位置
      node.position = {
        x: nodeWithPosition.x - nodeWidth / 2,
        y: nodeWithPosition.y - nodeHeight / 2,
      };
    });

    console.log('✅ Layout completed, sample node:', nodes[0]);
    return { nodes, edges };
  } catch (error) {
    console.error('❌ Error in dagre layout:', error);
    console.error('Error details:', error.message, error.stack);

    // 降级处理
    console.log('Using fallback layout...');
    const levelGroups = {};
    nodes.forEach(node => {
      const level = node.data.level || 0;
      if (!levelGroups[level]) levelGroups[level] = [];
      levelGroups[level].push(node);
    });

    Object.entries(levelGroups).forEach(([level, nodeList]) => {
      const x = parseInt(level) * 480;
      nodeList.forEach((node, index) => {
        node.position = { x, y: index * 260 };
        node.targetPosition = 'left';
        node.sourcePosition = 'right';
      });
    });

    return { nodes, edges };
  }
}

function transformData(data) {
  const nodes = [];
  const edges = [];

  const originalIdToCanvasId = {}; // 原始ID -> 画布ID的映射
  const canvasIdToNodeData = {}; // 避免重复创建相同的节点
  let analysisNodeCount = 0; // 用于给analysis节点添加X偏移

  // 创建节点
  Object.entries(data.nodes).forEach(([originalId, node]) => {
    // 统一处理所有类型的节点
    const nodeType = node.type || 'query';

    // 直接使用originalId作为canvasId，避免冲突
    const canvasId = originalId;

    originalIdToCanvasId[originalId] = canvasId;

    // 如果这个 canvasId 还没有创建过节点，则创建
    if (!canvasIdToNodeData[canvasId]) {
      canvasIdToNodeData[canvasId] = true;

      // 根据节点类型创建不同的数据结构
      if (nodeType === 'note' || nodeType === 'post') {
        nodes.push({
          id: canvasId,
          originalId: originalId,
          type: 'note',
          data: {
            title: node.query || node.title || '帖子',
            matchLevel: node.match_level,
            score: node.relevance_score ? node.relevance_score.toFixed(2) : '0.00',
            description: node.body_text || node.desc || '',
            isSelected: node.is_selected !== undefined ? node.is_selected : true,
            imageList: node.image_list || [],
            noteUrl: node.note_url || '',
            evaluationReason: node.evaluationReason || node.evaluation_reason || '',
            interact_info: node.interact_info || {},
            nodeType: nodeType,
            // 🆕 添加评估字段
            is_knowledge: node.is_knowledge !== undefined ? node.is_knowledge : null,
            knowledge_reason: node.knowledge_reason || '',
            post_relevance_score: node.post_relevance_score !== undefined ? node.post_relevance_score : null,
            relevance_level: node.relevance_level || '',
            relevance_reason: node.relevance_reason || ''
          },
          position: { x: 0, y: 0 },
        });
      } else if (nodeType === 'analysis') {
        // AI分析节点 - 添加X偏移避免叠加
        const xOffset = analysisNodeCount * 150; // 每个节点偏移150px
        analysisNodeCount++;

        nodes.push({
          id: canvasId,
          originalId: originalId,
          type: 'analysis',
          data: {
            query: node.query || '[AI分析]',
            note_id: node.note_id,
            note_url: node.note_url,
            title: node.title || '',
            body_text: node.body_text || '',
            interact_info: node.interact_info || {},
            extraction: node.extraction || null,
            image_list: node.image_list || [],
          },
          position: { x: xOffset, y: 0 },
        });
      } else {
        // query, seg, q, search, root 等节点
        let displayTitle = node.query || originalId;

        nodes.push({
          id: canvasId,
          originalId: originalId,
          type: 'query', // 使用 query 组件渲染所有非note节点
          data: {
            title: displayTitle,
            level: node.level || 0,
            score: node.relevance_score ? node.relevance_score.toFixed(2) : '0.00',
            strategy: node.strategy || '',
            parent: node.parent_query || '',
            isSelected: node.is_selected !== undefined ? node.is_selected : true,
            evaluationReason: node.evaluationReason || node.evaluation_reason || '',
            nodeType: nodeType, // 传递实际节点类型用于样式
            searchCount: node.search_count, // search 节点特有
            totalPosts: node.total_posts, // search 节点特有
            selectedWord: node.selected_word || '', // 加词节点特有 - 显示选择的词
            scoreColor: node.scoreColor || null,        // SUG节点的颜色标识
            parentQScore: node.parentQScore || 0,       // 父Q得分（用于调试）
            domain_index: node.domain_index !== undefined ? node.domain_index : null, // 域索引
            domain_type: node.domain_type || '', // 域类型（如"中心名词"、"核心动作"），只有Q节点有，segment节点不显示
            segment_type: node.segment_type || '', // segment类型（只有segment节点才有）
            type_label: node.type_label || '', // 类型标签
            domains: node.domains || [], // 域索引数组（domain_combination节点特有）
            domains_str: node.domains_str || '', // 域标识字符串（如"D0,D1"）
            from_segments: node.from_segments || [], // 来源segments（domain_combination节点特有）
            source_word_details: node.source_word_details || [], // 组合来源词及其得分
            source_scores: node.source_scores || [], // 扁平来源得分
            is_above_sources: node.is_above_sources || false, // 组合是否高于来源得分
            max_source_score: node.max_source_score !== undefined ? node.max_source_score : null, // 来源最高分
            item_type: node.item_type || '', // 构建下一轮节点来源类型
            is_suggestion: node.is_suggestion || false,
            suggestion_label: node.suggestion_label || '',
          },
          position: { x: 0, y: 0 },
        });
      }
    }
  });

  // 创建边 - 使用虚线样式，映射到画布ID
  data.edges.forEach((edge, index) => {
    const edgeColors = {
      '初始分词': '#10b981',
      '调用sug': '#06b6d4',
      '同义改写': '#f59e0b',
      '加词': '#3b82f6',
      '抽象改写': '#8b5cf6',
      '基于部分匹配改进': '#ec4899',
      '结果分支-抽象改写': '#a855f7',
      '结果分支-同义改写': '#fb923c',
      'query_to_note': '#ec4899',
    };

    const color = edgeColors[edge.strategy] || edgeColors[edge.edge_type] || '#d1d5db';
    const isNoteEdge = edge.edge_type === 'query_to_note';

    edges.push({
      id: `edge-${index}`,
      source: originalIdToCanvasId[edge.from], // 使用画布ID
      target: originalIdToCanvasId[edge.to],   // 使用画布ID
      type: 'simplebezier', // 使用简单贝塞尔曲线
      animated: isNoteEdge,
      style: {
        stroke: color,
        strokeWidth: isNoteEdge ? 2.5 : 2,
        strokeDasharray: isNoteEdge ? '5,5' : '8,4',
      },
      markerEnd: {
        type: 'arrowclosed',
        color: color,
        width: 20,
        height: 20,
      },
    });
  });

  // 使用 dagre 自动计算布局 - 从左到右
  return getLayoutedElements(nodes, edges, 'LR');
}

function FlowContent() {
  // 画布使用简化数据
  const { nodes: initialNodes, edges: initialEdges } = useMemo(() => {
    console.log('🔍 Transforming data for canvas...');
    const result = transformData(data);
    console.log('✅ Canvas data:', result.nodes.length, 'nodes,', result.edges.length, 'edges');
    return result;
  }, []);

  // 目录使用完整数据（如果存在）
  const { nodes: fullNodes, edges: fullEdges } = useMemo(() => {
    if (data.fullData) {
      console.log('🔍 Transforming full data for tree directory...');
      const result = transformData(data.fullData);
      console.log('✅ Directory data:', result.nodes.length, 'nodes,', result.edges.length, 'edges');
      return result;
    }
    // 如果没有 fullData，使用简化数据
    return { nodes: initialNodes, edges: initialEdges };
  }, [initialNodes, initialEdges]);

  // 初始化：找出所有有子节点的节点，默认折叠（画布节点）
  const initialCollapsedNodes = useMemo(() => {
    const nodesWithChildren = new Set();
    initialEdges.forEach(edge => {
      nodesWithChildren.add(edge.source);
    });
    // 排除根节点（level 0），让根节点默认展开
    const rootNode = initialNodes.find(n => n.data.level === 0);
    if (rootNode) {
      nodesWithChildren.delete(rootNode.id);
    }
    return nodesWithChildren;
  }, [initialNodes, initialEdges]);

  // 树节点的折叠状态需要在树构建后初始化
  const [collapsedNodes, setCollapsedNodes] = useState(() => initialCollapsedNodes);
  const [collapsedTreeNodes, setCollapsedTreeNodes] = useState(new Set());
  const [selectedNodeId, setSelectedNodeId] = useState(null);
  const [hiddenNodes, setHiddenNodes] = useState(new Set()); // 用户手动隐藏的节点
  const [focusMode, setFocusMode] = useState(false); // 全局聚焦模式，默认关闭
  const [focusedNodeId, setFocusedNodeId] = useState(null); // 单独聚焦的节点ID
  const [sidebarWidth, setSidebarWidth] = useState(400); // 左侧目录宽度
  const [isResizing, setIsResizing] = useState(false); // 是否正在拖拽调整宽度

  // 拖拽调整侧边栏宽度的处理逻辑
  const handleMouseDown = useCallback(() => {
    setIsResizing(true);
  }, []);

  useEffect(() => {
    if (!isResizing) return;

    const handleMouseMove = (e) => {
      const newWidth = e.clientX;
      // 限制宽度范围：300px - 700px
      if (newWidth >= 300 && newWidth <= 700) {
        setSidebarWidth(newWidth);
      }
    };

    const handleMouseUp = () => {
      setIsResizing(false);
    };

    document.addEventListener('mousemove', handleMouseMove);
    document.addEventListener('mouseup', handleMouseUp);

    return () => {
      document.removeEventListener('mousemove', handleMouseMove);
      document.removeEventListener('mouseup', handleMouseUp);
    };
  }, [isResizing]);

  // 获取 React Flow 实例以控制画布
  const { setCenter, fitView } = useReactFlow();

  // 获取某个节点的所有后代节点ID
  const getDescendants = useCallback((nodeId) => {
    const descendants = new Set();
    const queue = [nodeId];

    while (queue.length > 0) {
      const current = queue.shift();
      initialEdges.forEach(edge => {
        if (edge.source === current && !descendants.has(edge.target)) {
          descendants.add(edge.target);
          queue.push(edge.target);
        }
      });
    }

    return descendants;
  }, [initialEdges]);

  // 获取直接父节点
  const getDirectParents = useCallback((nodeId) => {
    const parents = [];
    initialEdges.forEach(edge => {
      if (edge.target === nodeId) {
        parents.push(edge.source);
      }
    });
    return parents;
  }, [initialEdges]);

  // 获取直接子节点
  const getDirectChildren = useCallback((nodeId) => {
    const children = [];
    initialEdges.forEach(edge => {
      if (edge.source === nodeId) {
        children.push(edge.target);
      }
    });
    return children;
  }, [initialEdges]);

  // 切换节点折叠状态
  const toggleNodeCollapse = useCallback((nodeId) => {
    setCollapsedNodes(prev => {
      const newSet = new Set(prev);
      const descendants = getDescendants(nodeId);

      if (newSet.has(nodeId)) {
        // 展开：移除此节点，但保持其他折叠的节点
        newSet.delete(nodeId);
      } else {
        // 折叠：添加此节点
        newSet.add(nodeId);
      }

      return newSet;
    });
  }, [getDescendants]);

  // 过滤可见的节点和边，并重新计算布局
  const { nodes, edges } = useMemo(() => {
    const nodesToHide = new Set();

    // 判断使用哪个节点ID进行聚焦：优先使用单独聚焦的节点，否则使用全局聚焦模式的选中节点
    const effectiveFocusNodeId = focusedNodeId || (focusMode ? selectedNodeId : null);

    // 聚焦模式：只显示聚焦节点、其父节点和直接子节点
    if (effectiveFocusNodeId) {
      const visibleInFocus = new Set([effectiveFocusNodeId]);

      // 添加所有父节点
      initialEdges.forEach(edge => {
        if (edge.target === effectiveFocusNodeId) {
          visibleInFocus.add(edge.source);
        }
      });

      // 添加所有直接子节点
      initialEdges.forEach(edge => {
        if (edge.source === effectiveFocusNodeId) {
          visibleInFocus.add(edge.target);
        }
      });

      // 隐藏不在聚焦范围内的节点
      initialNodes.forEach(node => {
        if (!visibleInFocus.has(node.id)) {
          nodesToHide.add(node.id);
        }
      });
    } else {
      // 非聚焦模式：使用原有的折叠逻辑
      // 收集所有被折叠节点的后代
      collapsedNodes.forEach(collapsedId => {
        const descendants = getDescendants(collapsedId);
        descendants.forEach(id => nodesToHide.add(id));
      });
    }

    // 添加用户手动隐藏的节点
    hiddenNodes.forEach(id => nodesToHide.add(id));

    const visibleNodes = initialNodes
      .filter(node => !nodesToHide.has(node.id))
      .map(node => ({
        ...node,
        data: {
          ...node.data,
          isCollapsed: collapsedNodes.has(node.id),
          hasChildren: initialEdges.some(e => e.source === node.id),
          onToggleCollapse: () => toggleNodeCollapse(node.id),
          onHideSelf: () => {
            setHiddenNodes(prev => {
              const newSet = new Set(prev);
              newSet.add(node.id);
              return newSet;
            });
          },
          onFocus: () => {
            // 切换聚焦状态
            if (focusedNodeId === node.id) {
              setFocusedNodeId(null); // 如果已经聚焦，则取消聚焦
            } else {
              // 先取消之前的聚焦，然后聚焦到当前节点
              setFocusedNodeId(node.id);

              // 延迟聚焦视图到该节点
              setTimeout(() => {
                fitView({
                  nodes: [{ id: node.id }],
                  duration: 800,
                  padding: 0.3,
                });
              }, 100);
            }
          },
          isFocused: focusedNodeId === node.id,
          isHighlighted: selectedNodeId === node.id,
        }
      }));

    const visibleEdges = initialEdges.filter(
      edge => !nodesToHide.has(edge.source) && !nodesToHide.has(edge.target)
    );

    // 重新计算布局 - 只对可见节点
    if (typeof window !== 'undefined' && typeof window.dagre !== 'undefined') {
      try {
        const dagreGraph = new window.dagre.graphlib.Graph();
        dagreGraph.setDefaultEdgeLabel(() => ({}));

        dagreGraph.setGraph({
          rankdir: 'LR',
          nodesep: 180,   // 垂直间距 - 增加以避免节点重叠
          ranksep: 360,  // 水平间距 - 增加以容纳更宽的节点
        });

        visibleNodes.forEach((node) => {
          let nodeWidth = 320;
          let nodeHeight = 220;

          // note 节点有轮播图，需要更大的空间
          if (node.type === 'note') {
            nodeWidth = 360;
            nodeHeight = 380;
          }

          dagreGraph.setNode(node.id, { width: nodeWidth, height: nodeHeight });
        });

        visibleEdges.forEach((edge) => {
          dagreGraph.setEdge(edge.source, edge.target);
        });

        window.dagre.layout(dagreGraph);

        visibleNodes.forEach((node) => {
          const nodeWithPosition = dagreGraph.node(node.id);
          if (nodeWithPosition) {
            // 根据节点类型获取对应的尺寸
            let nodeWidth = 320;
            let nodeHeight = 220;
            if (node.type === 'note') {
              nodeWidth = 360;
              nodeHeight = 380;
            }

            node.position = {
              x: nodeWithPosition.x - nodeWidth / 2,
              y: nodeWithPosition.y - nodeHeight / 2,
            };
            node.targetPosition = 'left';
            node.sourcePosition = 'right';
          }
        });

        console.log('✅ Dynamic layout recalculated for', visibleNodes.length, 'visible nodes');
      } catch (error) {
        console.error('❌ Error in dynamic layout:', error);
      }
    }

    return { nodes: visibleNodes, edges: visibleEdges };
  }, [initialNodes, initialEdges, collapsedNodes, hiddenNodes, focusMode, focusedNodeId, getDescendants, toggleNodeCollapse, selectedNodeId]);

  // 构建树形结构 - 允许一个节点有多个父节点
  // 为目录构建树（使用完整数据）
  const buildTree = useCallback(() => {
    // 使用完整数据构建目录树
    const nodeMap = new Map();
    fullNodes.forEach(node => {
      nodeMap.set(node.id, node);
    });

    // 为每个节点创建树节点的副本（允许多次出现）
    const createTreeNode = (nodeId, pathKey) => {
      const node = nodeMap.get(nodeId);
      if (!node) return null;

      return {
        ...node,
        treeKey: pathKey, // 唯一的树路径key，用于React key
        children: []
      };
    };

    // 构建父子关系映射：记录每个节点的所有父节点，去重边
    const parentToChildren = new Map();
    const childToParents = new Map();

    fullEdges.forEach(edge => {
      // 记录父->子关系（去重：同一个父节点到同一个子节点只记录一次）
      if (!parentToChildren.has(edge.source)) {
        parentToChildren.set(edge.source, []);
      }
      const children = parentToChildren.get(edge.source);
      if (!children.includes(edge.target)) {
        children.push(edge.target);
      }

      // 记录子->父关系（用于判断是否有多个父节点，也去重）
      if (!childToParents.has(edge.target)) {
        childToParents.set(edge.target, []);
      }
      const parents = childToParents.get(edge.target);
      if (!parents.includes(edge.source)) {
        parents.push(edge.source);
      }
    });

    // 递归构建树
    const buildSubtree = (nodeId, pathKey, visitedInPath) => {
      // 避免循环引用：如果当前路径中已经访问过这个节点，跳过
      if (visitedInPath.has(nodeId)) {
        return null;
      }

      const treeNode = createTreeNode(nodeId, pathKey);
      if (!treeNode) return null;

      const newVisitedInPath = new Set(visitedInPath);
      newVisitedInPath.add(nodeId);

      const children = parentToChildren.get(nodeId) || [];
      treeNode.children = children
        .map((childId, index) => buildSubtree(childId, pathKey + '-' + childId + '-' + index, newVisitedInPath))
        .filter(child => child !== null);

      return treeNode;
    };

    // 找出所有根节点（没有入边的节点）
    const hasParent = new Set();
    fullEdges.forEach(edge => {
      hasParent.add(edge.target);
    });

    const roots = [];
    fullNodes.forEach((node, index) => {
      if (!hasParent.has(node.id)) {
        const treeNode = buildSubtree(node.id, 'root-' + node.id + '-' + index, new Set());
        if (treeNode) roots.push(treeNode);
      }
    });

    return roots;
  }, [fullNodes, fullEdges]);

  const treeRoots = useMemo(() => buildTree(), [buildTree]);

  // 生成树形文本结构（使用完整数据）
  const generateTreeText = useCallback(() => {
    const lines = [];

    // 递归生成树形文本
    const traverse = (nodes, prefix = '', isLast = true, depth = 0) => {
      nodes.forEach((node, index) => {
        const isLastNode = index === nodes.length - 1;
        const nodeData = fullNodes.find(n => n.id === node.id)?.data || {};
        const nodeType = nodeData.nodeType || node.data?.nodeType || 'unknown';
        const title = nodeData.title || node.data?.title || node.id;

        // 优先从node.data获取score，然后从nodeData获取
        let score = null;
        if (node.data?.score !== undefined && node.data?.score !== null) {
          score = node.data.score;
        } else if (node.data?.relevance_score !== undefined && node.data?.relevance_score !== null) {
          score = node.data.relevance_score;
        } else if (nodeData.score !== undefined && nodeData.score !== null) {
          score = nodeData.score;
        } else if (nodeData.relevance_score !== undefined && nodeData.relevance_score !== null) {
          score = nodeData.relevance_score;
        }

        const strategy = nodeData.strategy || node.data?.strategy || '';

        // 构建当前行 - score可能是数字或字符串，step/round节点不显示分数
        const connector = isLastNode ? '└─' : '├─';
        let scoreText = '';
        if (nodeType !== 'step' && nodeType !== 'round' && score !== null && score !== undefined) {
          // score可能已经是字符串格式（如 "0.05"），也可能是数字
          const scoreStr = typeof score === 'number' ? score.toFixed(2) : score;
          scoreText = ` (分数: ${scoreStr})`;
        }
        const strategyText = strategy ? ` [${strategy}]` : '';

        lines.push(`${prefix}${connector} ${title}${scoreText}${strategyText}`);

        // 递归处理子节点
        if (node.children && node.children.length > 0) {
          const childPrefix = prefix + (isLastNode ? '   ' : '│  ');
          traverse(node.children, childPrefix, isLastNode, depth + 1);
        }
      });
    };

    // 添加标题
    const rootNode = fullNodes.find(n => n.data?.level === 0);
    if (rootNode) {
      lines.push(`📊 查询扩展树形结构`);
      lines.push(`原始问题: ${rootNode.data.title || rootNode.data.query}`);
      lines.push('');
    }

    traverse(treeRoots);

    return lines.join('\n');
  }, [treeRoots, fullNodes]);

  // 复制树形结构到剪贴板
  const copyTreeToClipboard = useCallback(async () => {
    try {
      const treeText = generateTreeText();
      await navigator.clipboard.writeText(treeText);
      alert('✅ 树形结构已复制到剪贴板！');
    } catch (err) {
      console.error('复制失败:', err);
      alert('❌ 复制失败，请手动复制');
    }
  }, [generateTreeText]);

  // 初始化树节点折叠状态
  useEffect(() => {
    const getAllTreeKeys = (nodes) => {
      const keys = new Set();
      const traverse = (node) => {
        if (node.children && node.children.length > 0) {
          // 排除根节点
          if (node.data.level !== 0) {
            keys.add(node.treeKey);
          }
          node.children.forEach(traverse);
        }
      };
      nodes.forEach(traverse);
      return keys;
    };

    setCollapsedTreeNodes(getAllTreeKeys(treeRoots));
  }, [treeRoots]);

  // 映射完整节点ID到画布简化节点ID
  const mapTreeNodeToCanvasNode = useCallback((treeNodeId) => {
    // 如果是简化模式，需要映射
    if (data.fullData) {
      // 从完整数据中找到节点
      const fullNode = fullNodes.find(n => n.id === treeNodeId);
      if (!fullNode) return treeNodeId;

      // 根据节点类型和文本找到画布上的简化节点
      const nodeText = fullNode.data.title || fullNode.data.query;
      const nodeType = fullNode.data.nodeType || fullNode.type;

      // Query类节点：找 query_xxx
      if (['q', 'seg', 'sug', 'add_word', 'query'].includes(nodeType)) {
        const canvasNode = initialNodes.find(n =>
          (n.data.title === nodeText || n.data.query === nodeText) &&
          ['query'].includes(n.type)
        );
        return canvasNode ? canvasNode.id : treeNodeId;
      }

      // Post节点：按note_id查找
      if (nodeType === 'post' || nodeType === 'note') {
        const noteId = fullNode.data.note_id;
        if (noteId) {
          const canvasNode = initialNodes.find(n => n.data.note_id === noteId);
          return canvasNode ? canvasNode.id : treeNodeId;
        }
      }

      // 其他节点类型（Round/Step等）：直接返回
      return treeNodeId;
    }

    // 非简化模式，直接返回
    return treeNodeId;
  }, [data.fullData, fullNodes, initialNodes]);

  const renderTree = useCallback((treeNodes, level = 0) => {
    return treeNodes.map(node => {
      // 使用 treeKey 来区分树中的不同实例
      const isCollapsed = collapsedTreeNodes.has(node.treeKey);
      const isSelected = selectedNodeId === node.id;

      return (
        <TreeNode
          key={node.treeKey}
          node={node}
          level={level}
          isCollapsed={isCollapsed}
          isSelected={isSelected}
          onToggle={() => {
            setCollapsedTreeNodes(prev => {
              const newSet = new Set(prev);
              if (newSet.has(node.treeKey)) {
                newSet.delete(node.treeKey);
              } else {
                newSet.add(node.treeKey);
              }
              return newSet;
            });
          }}
          onSelect={() => {
            // 将目录节点ID映射到画布节点ID
            const treeNodeId = node.id;
            const canvasNodeId = mapTreeNodeToCanvasNode(treeNodeId);

            // 检查画布上是否存在这个节点
            const canvasNodeExists = initialNodes.some(n => n.id === canvasNodeId);
            if (!canvasNodeExists) {
              console.warn(`节点 ${canvasNodeId} 在画布上不存在（可能被简化了）`);
              return;
            }

            const nodeId = canvasNodeId;

            // 展开所有祖先节点
            const ancestorIds = [nodeId];
            const findAncestors = (id) => {
              initialEdges.forEach(edge => {
                if (edge.target === id && !ancestorIds.includes(edge.source)) {
                  ancestorIds.push(edge.source);
                  findAncestors(edge.source);
                }
              });
            };
            findAncestors(nodeId);

            // 如果节点或其祖先被隐藏，先恢复它们
            setHiddenNodes(prev => {
              const newSet = new Set(prev);
              ancestorIds.forEach(id => newSet.delete(id));
              return newSet;
            });

            setSelectedNodeId(nodeId);

            // 获取选中节点的直接子节点
            const childrenIds = [];
            initialEdges.forEach(edge => {
              if (edge.source === nodeId) {
                childrenIds.push(edge.target);
              }
            });

            setCollapsedNodes(prev => {
              const newSet = new Set(prev);
              // 展开所有祖先节点
              ancestorIds.forEach(id => newSet.delete(id));
              // 展开选中节点本身
              newSet.delete(nodeId);
              // 展开选中节点的直接子节点
              childrenIds.forEach(id => newSet.delete(id));
              return newSet;
            });

            // 延迟聚焦，等待节点展开和布局重新计算
            setTimeout(() => {
              fitView({
                nodes: [{ id: nodeId }],
                duration: 800,
                padding: 0.3,
              });
            }, 300);
          }}
        >
          {node.children && node.children.length > 0 && renderTree(node.children, level + 1)}
        </TreeNode>
      );
    });
  }, [collapsedTreeNodes, selectedNodeId, nodes, setCenter, initialEdges, setCollapsedNodes, fitView, mapTreeNodeToCanvasNode, initialNodes, setHiddenNodes]);

  console.log('📊 Rendering with', nodes.length, 'visible nodes and', edges.length, 'visible edges');

  if (nodes.length === 0) {
    return (
      <div style={{ padding: 50, color: 'red', fontSize: 20 }}>
        ERROR: No nodes to display!
      </div>
    );
  }

  return (
    <div style={{ width: '100vw', height: '100vh', background: '#f9fafb', display: 'flex', flexDirection: 'column' }}>
      {/* 顶部面包屑导航栏 */}
      <div style={{
        minHeight: '48px',
        maxHeight: '120px',
        background: 'white',
        borderBottom: '1px solid #e5e7eb',
        display: 'flex',
        alignItems: 'flex-start',
        padding: '12px 24px',
        zIndex: 1000,
        boxShadow: '0 1px 3px rgba(0, 0, 0, 0.05)',
        flexShrink: 0,
        overflowY: 'auto',
      }}>
        <div style={{ width: '100%' }}>
          {selectedNodeId ? (
            <div style={{ fontSize: '12px', color: '#6b7280' }}>
              {/* 面包屑导航 - 显示所有路径 */}
              {(() => {
                const selectedNode = nodes.find(n => n.id === selectedNodeId);
                if (!selectedNode) return null;

                // 找到所有从根节点到当前节点的路径
                const findAllPaths = (targetId) => {
                  const paths = [];

                  const buildPath = (nodeId, currentPath) => {
                    const node = initialNodes.find(n => n.id === nodeId);
                    if (!node) return;

                    const newPath = [node, ...currentPath];

                    // 找到所有父节点
                    const parents = initialEdges.filter(e => e.target === nodeId).map(e => e.source);

                    if (parents.length === 0) {
                      // 到达根节点
                      paths.push(newPath);
                    } else {
                      // 递归处理所有父节点
                      parents.forEach(parentId => {
                        buildPath(parentId, newPath);
                      });
                    }
                  };

                  buildPath(targetId, []);
                  return paths;
                };

                const allPaths = findAllPaths(selectedNodeId);

                // 去重：将路径转换为字符串进行比较
                const uniquePaths = [];
                const pathStrings = new Set();
                allPaths.forEach(path => {
                  const pathString = path.map(n => n.id).join('->');
                  if (!pathStrings.has(pathString)) {
                    pathStrings.add(pathString);
                    uniquePaths.push(path);
                  }
                });

                return (
                  <div style={{ display: 'flex', flexDirection: 'column', gap: '6px' }}>
                    {uniquePaths.map((path, pathIndex) => (
                      <div key={pathIndex} style={{ display: 'flex', alignItems: 'center', gap: '6px', flexWrap: 'wrap' }}>
                        {pathIndex > 0 && <span style={{ color: '#d1d5db', marginRight: '4px' }}>或</span>}
                        {path.map((node, index) => {
                          // 获取节点的 score、strategy 和 isSelected
                          const nodeScore = node.data.score ? parseFloat(node.data.score) : 0;
                          const nodeStrategy = getPrimaryStrategy(node.data);  // 使用智能提取函数
                          const strategyColor = getStrategyColor(nodeStrategy);
                          const nodeIsSelected = node.type === 'note' ? node.data.matchLevel !== 'unsatisfied' : node.data.isSelected !== false;
                          const nodeActualType = node.data.nodeType || node.type; // 获取实际节点类型

                          // 计算路径节点字体颜色：根据分数提升幅度判断
                          let pathFontColor = '#374151'; // 默认颜色
                          if (node.type === 'note') {
                            pathFontColor = node.data.matchLevel === 'unsatisfied' ? '#ef4444' : '#374151';
                          } else if (node.data.seed_score !== undefined) {
                            const parentScore = parseFloat(node.data.seed_score);
                            const gain = nodeScore - parentScore;
                            pathFontColor = gain >= 0.05 ? '#16a34a' : '#ef4444';
                          } else if (index > 0) {
                            const prevNode = path[index - 1];
                            const prevScore = prevNode.data.score ? parseFloat(prevNode.data.score) : 0;
                            const gain = nodeScore - prevScore;
                            pathFontColor = gain >= 0.05 ? '#16a34a' : '#ef4444';
                          } else if (node.data.isSelected === false) {
                            pathFontColor = '#ef4444';
                          }

                          return (
                          <React.Fragment key={node.id + '-' + index}>
                            <span
                              onClick={() => {
                                const nodeId = node.id;

                                // 找到所有祖先节点
                                const ancestorIds = [nodeId];
                                const findAncestors = (id) => {
                                  initialEdges.forEach(edge => {
                                    if (edge.target === id && !ancestorIds.includes(edge.source)) {
                                      ancestorIds.push(edge.source);
                                      findAncestors(edge.source);
                                    }
                                  });
                                };
                                findAncestors(nodeId);

                                // 如果节点或其祖先被隐藏，先恢复它们
                                setHiddenNodes(prev => {
                                  const newSet = new Set(prev);
                                  ancestorIds.forEach(id => newSet.delete(id));
                                  return newSet;
                                });

                                // 展开目录树中到达该节点的路径
                                // 需要找到所有包含该节点的树路径的 treeKey，并展开它们的父节点
                                setCollapsedTreeNodes(prev => {
                                  const newSet = new Set(prev);
                                  // 清空所有折叠状态，让目录树完全展开到选中节点
                                  // 这样可以确保选中节点在目录中可见
                                  return new Set();
                                });

                                setSelectedNodeId(nodeId);
                                setTimeout(() => {
                                  fitView({
                                    nodes: [{ id: nodeId }],
                                    duration: 800,
                                    padding: 0.3,
                                  });
                                }, 100);
                              }}
                              style={{
                                padding: '6px 8px',
                                borderRadius: '4px',
                                background: 'white',
                                border: index === path.length - 1 ? '2px solid #3b82f6' : '1px solid #d1d5db',
                                color: '#374151',
                                fontWeight: index === path.length - 1 ? '600' : '400',
                                width: '180px',
                                cursor: 'pointer',
                                transition: 'all 0.2s ease',
                                position: 'relative',
                                display: 'inline-flex',
                                flexDirection: 'column',
                                gap: '4px',
                              }}
                              onMouseEnter={(e) => {
                                e.currentTarget.style.opacity = '0.8';
                              }}
                              onMouseLeave={(e) => {
                                e.currentTarget.style.opacity = '1';
                              }}
                              title={`${node.data.title || node.id} (Score: ${nodeScore.toFixed(2)}, Strategy: ${nodeStrategy}, Selected: ${nodeIsSelected})`}
                            >
                              {/* 上半部分：竖线 + 图标 + 文字 + 分数 */}
                              <div style={{
                                display: 'flex',
                                alignItems: 'center',
                                gap: '6px',
                              }}>
                                {/* 策略类型竖线 */}
                                <div style={{
                                  width: '3px',
                                  height: '16px',
                                  background: strategyColor,
                                  borderRadius: '2px',
                                  flexShrink: 0,
                                }} />

                                {/* 节点文字 - 左侧 */}
                                <span style={{
                                  flex: 1,
                                  fontSize: '12px',
                                  color: pathFontColor,
                                  overflow: 'hidden',
                                  textOverflow: 'ellipsis',
                                  whiteSpace: 'nowrap',
                                }}>
                                  {node.data.title || node.id}
                                </span>

                                {/* 域标识 - 右侧,挨着分数 */}
                                {(node.data.domain_type || node.data.domains_str || (node.data.domain_index !== null && node.data.domain_index !== undefined)) && (
                                  <span style={{
                                    fontSize: '12px',
                                    color: '#fff',
                                    background: '#6366f1',
                                    padding: '2px 5px',
                                    borderRadius: '3px',
                                    flexShrink: 0,
                                    fontWeight: '600',
                                    marginLeft: '4px',
                                  }}
                                  title={
                                    node.data.domain_type ? '域: ' + node.data.domain_type + ' (D' + node.data.domain_index + ')' :
                                    node.data.domains_str ? '域: ' + node.data.domains_str :
                                    '域 D' + node.data.domain_index
                                  }
                                  >
                                    {node.data.domain_type || node.data.domains_str || ('D' + node.data.domain_index)}
                                  </span>
                                )}

                                {/* 分数显示 - 步骤和轮次节点不显示分数 */}
                                {nodeActualType !== 'step' && nodeActualType !== 'round' && (
                                  <span style={{
                                    fontSize: '10px',
                                    color: '#6b7280',
                                    fontWeight: '500',
                                    flexShrink: 0,
                                    minWidth: '35px',
                                    textAlign: 'right',
                                    marginLeft: '4px',
                                  }}>
                                    {nodeScore.toFixed(2)}
                                  </span>
                                )}
                              </div>

                              {/* 分数下划线 - 步骤和轮次节点不显示 */}
                              {nodeActualType !== 'step' && nodeActualType !== 'round' && (
                                <div style={{
                                  width: (nodeScore * 100) + '%',
                                  height: '2px',
                                  background: getScoreColor(nodeScore),
                                  borderRadius: '1px',
                                  marginLeft: '9px',
                                }} />
                              )}
                            </span>
                            {index < path.length - 1 && <span style={{ color: '#9ca3af' }}>›</span>}
                          </React.Fragment>
                        )})}
                      </div>
                    ))}
                  </div>
                );
              })()}
            </div>
          ) : (
            <div style={{ fontSize: '13px', color: '#9ca3af', textAlign: 'center' }}>
              选择一个节点查看路径
            </div>
          )}
        </div>
      </div>

      {/* 主内容区：目录 + 画布 */}
      <div style={{
        display: 'flex',
        flex: 1,
        overflow: 'hidden',
        cursor: isResizing ? 'col-resize' : 'default',
        userSelect: isResizing ? 'none' : 'auto',
      }}>
        {/* 左侧目录树 */}
        <div style={{
          width: `${sidebarWidth}px`,
          background: 'white',
          borderRight: '1px solid #e5e7eb',
          display: 'flex',
          flexDirection: 'column',
          flexShrink: 0,
        }}>
          <div style={{
            padding: '12px 16px',
            borderBottom: '1px solid #e5e7eb',
            display: 'flex',
            justifyContent: 'space-between',
            alignItems: 'center',
          }}>
            <span style={{
              fontWeight: '600',
              fontSize: '14px',
              color: '#111827',
            }}>
              节点目录
            </span>
            <div style={{ display: 'flex', gap: '6px' }}>
              <button
                onClick={() => {
                  setCollapsedTreeNodes(new Set());
                }}
                style={{
                  fontSize: '11px',
                  padding: '4px 8px',
                  borderRadius: '4px',
                  border: '1px solid #d1d5db',
                  background: 'white',
                  color: '#6b7280',
                  cursor: 'pointer',
                  fontWeight: '500',
                }}
                title="展开全部节点"
              >
                全部展开
              </button>
              <button
                onClick={() => {
                  const getAllTreeKeys = (nodes) => {
                    const keys = new Set();
                    const traverse = (node) => {
                      if (node.children && node.children.length > 0) {
                        keys.add(node.treeKey);
                        node.children.forEach(traverse);
                      }
                    };
                    nodes.forEach(traverse);
                    return keys;
                  };
                  setCollapsedTreeNodes(getAllTreeKeys(treeRoots));
                }}
                style={{
                  fontSize: '11px',
                  padding: '4px 8px',
                  borderRadius: '4px',
                  border: '1px solid #d1d5db',
                  background: 'white',
                  color: '#6b7280',
                  cursor: 'pointer',
                  fontWeight: '500',
                }}
                title="折叠全部节点"
              >
                全部折叠
              </button>
              <button
                onClick={copyTreeToClipboard}
                style={{
                  fontSize: '11px',
                  padding: '4px 8px',
                  borderRadius: '4px',
                  border: '1px solid #3b82f6',
                  background: '#3b82f6',
                  color: 'white',
                  cursor: 'pointer',
                  fontWeight: '500',
                  transition: 'all 0.2s',
                }}
                onMouseEnter={(e) => e.currentTarget.style.background = '#2563eb'}
                onMouseLeave={(e) => e.currentTarget.style.background = '#3b82f6'}
                title="复制树形结构为文本格式"
              >
                📋 复制树形结构
              </button>
            </div>
          </div>
          <div style={{
            flex: 1,
            overflowX: 'auto',
            overflowY: 'auto',
            padding: '8px',
          }}>
            <div style={{ minWidth: 'fit-content' }}>
              {renderTree(treeRoots)}
            </div>
          </div>
        </div>

        {/* 可拖拽的分隔条 */}
        <div
          onMouseDown={handleMouseDown}
          style={{
            width: '4px',
            cursor: 'col-resize',
            background: isResizing ? '#3b82f6' : 'transparent',
            transition: isResizing ? 'none' : 'background 0.2s',
            flexShrink: 0,
            position: 'relative',
          }}
          onMouseEnter={(e) => e.currentTarget.style.background = '#e5e7eb'}
          onMouseLeave={(e) => {
            if (!isResizing) e.currentTarget.style.background = 'transparent';
          }}
        >
          {/* 拖拽提示线 */}
          <div style={{
            position: 'absolute',
            top: '50%',
            left: '50%',
            transform: 'translate(-50%, -50%)',
            width: '1px',
            height: '40px',
            background: '#9ca3af',
            opacity: isResizing ? 1 : 0.3,
          }} />
        </div>

        {/* 画布区域 */}
        <div style={{ flex: 1, position: 'relative' }}>

          {/* 右侧图例 */}
          <div style={{
            position: 'absolute',
            top: '20px',
            right: '20px',
            background: 'white',
            padding: '16px',
            borderRadius: '12px',
            boxShadow: '0 4px 12px rgba(0, 0, 0, 0.08)',
            zIndex: 1000,
            maxWidth: '260px',
            border: '1px solid #e5e7eb',
          }}>
        <div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center', marginBottom: '12px' }}>
          <h3 style={{ fontSize: '14px', fontWeight: '600', color: '#111827', margin: 0 }}>图例</h3>
          <button
            onClick={() => setFocusMode(!focusMode)}
            style={{
              fontSize: '11px',
              padding: '4px 8px',
              borderRadius: '4px',
              border: '1px solid',
              borderColor: focusMode ? '#3b82f6' : '#d1d5db',
              background: focusMode ? '#3b82f6' : 'white',
              color: focusMode ? 'white' : '#6b7280',
              cursor: 'pointer',
              fontWeight: '500',
            }}
            title={focusMode ? '关闭聚焦模式' : '开启聚焦模式'}
          >
            {focusMode ? '🎯 聚焦' : '📊 全图'}
          </button>
        </div>

        <div style={{ fontSize: '12px' }}>
          {/* 画布节点展开/折叠控制 */}
          <div style={{ marginBottom: '12px', paddingBottom: '12px', borderBottom: '1px solid #f3f4f6' }}>
            <div style={{ fontSize: '12px', fontWeight: '500', marginBottom: '8px', color: '#374151' }}>节点控制</div>
            <div style={{ display: 'flex', gap: '6px' }}>
              <button
                onClick={() => {
                  setCollapsedNodes(new Set());
                }}
                style={{
                  fontSize: '11px',
                  padding: '4px 8px',
                  borderRadius: '4px',
                  border: '1px solid #d1d5db',
                  background: 'white',
                  color: '#6b7280',
                  cursor: 'pointer',
                  fontWeight: '500',
                  flex: 1,
                }}
                title="展开画布中所有节点的子节点"
              >
                全部展开
              </button>
              <button
                onClick={() => {
                  const allNodeIds = new Set(initialNodes.map(n => n.id));
                  setCollapsedNodes(allNodeIds);
                }}
                style={{
                  fontSize: '11px',
                  padding: '4px 8px',
                  borderRadius: '4px',
                  border: '1px solid #d1d5db',
                  background: 'white',
                  color: '#6b7280',
                  cursor: 'pointer',
                  fontWeight: '500',
                  flex: 1,
                }}
                title="折叠画布中所有节点的子节点"
              >
                全部折叠
              </button>
            </div>
          </div>

          <div style={{ paddingTop: '12px', borderTop: '1px solid #f3f4f6' }}>
            <div style={{ fontSize: '12px', fontWeight: '500', marginBottom: '8px', color: '#374151' }}>策略类型</div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#10b981', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>初始分词</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#06b6d4', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>调用sug</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#f59e0b', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>同义改写</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#3b82f6', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>加词</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#8b5cf6', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>抽象改写</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#ec4899', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>基于部分匹配改进</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#a855f7', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>结果分支-抽象改写</span>
            </div>
            <div style={{ display: 'flex', alignItems: 'center', margin: '6px 0' }}>
              <div style={{ width: '20px', height: '2px', marginRight: '8px', background: '#fb923c', opacity: 0.7 }}></div>
              <span style={{ color: '#6b7280', fontSize: '11px' }}>结果分支-同义改写</span>
            </div>
          </div>

          <div style={{
            marginTop: '12px',
            paddingTop: '12px',
            borderTop: '1px solid #f3f4f6',
            fontSize: '11px',
            color: '#9ca3af',
            lineHeight: '1.5',
          }}>
            💡 点击节点左上角 × 隐藏节点
          </div>

          {/* 隐藏节点列表 - 在图例内部 */}
          {hiddenNodes.size > 0 && (
            <div style={{
              marginTop: '12px',
              paddingTop: '12px',
              borderTop: '1px solid #f3f4f6',
            }}>
              <div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center', marginBottom: '8px' }}>
                <h4 style={{ fontSize: '12px', fontWeight: '600', color: '#111827' }}>已隐藏节点</h4>
                <button
                  onClick={() => setHiddenNodes(new Set())}
                  style={{
                    fontSize: '10px',
                    color: '#3b82f6',
                    background: 'none',
                    border: 'none',
                    cursor: 'pointer',
                    textDecoration: 'underline',
                  }}
                >
                  全部恢复
                </button>
              </div>
              <div style={{ fontSize: '12px', maxHeight: '200px', overflow: 'auto' }}>
                {Array.from(hiddenNodes).map(nodeId => {
                  const node = initialNodes.find(n => n.id === nodeId);
                  if (!node) return null;
                  return (
                    <div
                      key={nodeId}
                      style={{
                        display: 'flex',
                        justifyContent: 'space-between',
                        alignItems: 'center',
                        padding: '6px 8px',
                        margin: '4px 0',
                        background: '#f9fafb',
                        borderRadius: '6px',
                        fontSize: '11px',
                      }}
                    >
                      <span
                        style={{
                          flex: 1,
                          overflow: 'hidden',
                          textOverflow: 'ellipsis',
                          whiteSpace: 'nowrap',
                          color: '#374151',
                        }}
                        title={node.data.title || nodeId}
                      >
                        {node.data.title || nodeId}
                      </span>
                      <button
                        onClick={() => {
                          setHiddenNodes(prev => {
                            const newSet = new Set(prev);
                            newSet.delete(nodeId);
                            return newSet;
                          });
                        }}
                        style={{
                          marginLeft: '8px',
                          fontSize: '10px',
                          color: '#10b981',
                          background: 'none',
                          border: 'none',
                          cursor: 'pointer',
                          flexShrink: 0,
                        }}
                      >
                        恢复
                      </button>
                    </div>
                  );
                })}
              </div>
            </div>
          )}
          </div>
          </div>

          {/* React Flow 画布 */}
          <ReactFlow
            nodes={nodes}
            edges={edges}
            nodeTypes={nodeTypes}
            fitView
            fitViewOptions={{ padding: 0.2, duration: 500 }}
            minZoom={0.1}
            maxZoom={1.5}
            nodesDraggable={true}
            nodesConnectable={false}
            elementsSelectable={true}
            defaultEdgeOptions={{
              type: 'smoothstep',
            }}
            proOptions={{ hideAttribution: true }}
            onNodeClick={(event, clickedNode) => {
              setSelectedNodeId(clickedNode.id);
            }}
          >
            <Controls style={{ bottom: '20px', left: 'auto', right: '20px' }} />
            <Background variant="dots" gap={20} size={1} color="#e5e7eb" />
          </ReactFlow>
        </div>
      </div>
    </div>
  );
}

function App() {
  return (
    <ReactFlowProvider>
      <FlowContent />
    </ReactFlowProvider>
  );
}

const root = createRoot(document.getElementById('root'));
root.render(<App />);