feat: 更新分层实验映射（ab/34/67/5d 0417起切回str*ros），新增探查与诊断SQL

- DNN模型-调参实验截止20260416，20260417起切回变更str*ros建模目标实验
- 新增分享链深度、外部流量来源、渠道lift、重复推荐率探查SQL
- 新增模型预估诊断v1 SQL

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

tasks/00_尾号实验/base_all_new_v3_分层.sql

@@ -65,24 +65,25 @@ WITH t_suffix_group AS
     UNION ALL SELECT "4", "89", "对照组",                          "20260301", "299991231"
 
 
-    
-
-
     -- ── apptype = 0 ──────────────────────────────────────────────────
-    UNION ALL SELECT "0", "ab", "实验组：变更str*ros建模目标实验 有问题", "20260413", "29991231"
-    UNION ALL SELECT "0", "ab", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "ab", "实验组：变更str*ros建模目标实验 有问题", "20260413", "20260415"
+    UNION ALL SELECT "0", "ab", "实验组：DNN模型-调参", "20260416", "20260416"
+    UNION ALL SELECT "0", "ab", "实验组：变更str*ros建模目标实验", "20260417", "29991231"
     UNION ALL SELECT "0", "01", "实验组：变更str*ros建模目标实验", "20260320", "20260410"
     UNION ALL SELECT "0", "01", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
     UNION ALL SELECT "0", "01", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
     UNION ALL SELECT "0", "34", "实验组：变更str*ros建模目标实验", "20260330", "20260410"
     UNION ALL SELECT "0", "34", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
-    UNION ALL SELECT "0", "34", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "34", "实验组：DNN模型-调参", "20260416", "20260416"
+    UNION ALL SELECT "0", "34", "实验组：变更str*ros建模目标实验", "20260417", "29991231"
     UNION ALL SELECT "0", "67", "实验组：变更str*ros建模目标实验", "20260330", "20260410"
     UNION ALL SELECT "0", "67", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
-    UNION ALL SELECT "0", "67", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "67", "实验组：DNN模型-调参", "20260416", "20260416"
+    UNION ALL SELECT "0", "67", "实验组：变更str*ros建模目标实验", "20260417", "29991231"
     UNION ALL SELECT "0", "5d", "实验组：变更str*ros建模目标实验", "20260407", "20260410"
     UNION ALL SELECT "0", "5d", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
-    UNION ALL SELECT "0", "5d", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "5d", "实验组：DNN模型-调参", "20260416", "20260416"
+    UNION ALL SELECT "0", "5d", "实验组：变更str*ros建模目标实验", "20260417", "29991231"
     UNION ALL SELECT "0", "ef", "实验组：DNN模型-调参",            "20260410", "29991231"
     UNION ALL SELECT "0", "2c", "实验组：DNN模型",                 "20260413", "29991231"
     UNION ALL SELECT "0", "89", "对照组",                          "20260301", "29991231"

tasks/00_尾号实验/探查_分享链深度.sql

@@ -0,0 +1,26 @@
+-- 验证假设：产品 0 (vlog) 的分享链是否比产品 4 (iLife) 更深？
+-- 同时对比 异常期(0411-0415) vs 正常期(0408-0410) 的链深度变化
+-- 跑法：python fetch_daily.py tasks/00_尾号实验/探查_分享链深度.sql --start 20260408 --end 20260415 --force
+--
+-- 注意：click 事件的 pagesource 和 share 不同，所以不在 click 上 filter pagesource
+-- 用 pagesource 前缀（vlog / iLife）推断 apptype，对 click 事件也适用
+
+SELECT  CASE WHEN pagesource LIKE 'vlog%'  THEN '0'
+             WHEN pagesource LIKE 'iLife%' THEN '4'
+             ELSE 'other'
+        END AS apptype
+        ,topic
+        ,sharedepth
+        ,COUNT(1) AS event_cnt
+        ,COUNT(DISTINCT machinecode) AS unique_users
+FROM    loghubods.user_share_log
+WHERE   dt = '${dt}'
+AND     topic IN ('share', 'click')
+AND     (pagesource LIKE 'vlog%' OR pagesource LIKE 'iLife%')  -- 只看 vlog/iLife 两个产品
+GROUP BY CASE WHEN pagesource LIKE 'vlog%'  THEN '0'
+              WHEN pagesource LIKE 'iLife%' THEN '4'
+              ELSE 'other'
+         END
+         ,topic
+         ,sharedepth
+;

tasks/00_尾号实验/探查_外部流量来源.sql

@@ -0,0 +1,27 @@
+-- 探查 apptype=0 和 apptype=4 外部流量里，rootsourceid 前缀 × pagesource 的分布
+-- 只按 (apptype, rootsourceid_prefix, pagesource, layer_type) 分组，避免 LIMIT 吃不下
+-- 跑法：python fetch_daily.py tasks/00_尾号实验/探查_外部流量来源.sql --date 20260410 --force
+
+SELECT  apptype
+        ,CASE WHEN rootsourceid = '' OR rootsourceid IS NULL THEN '内部'
+              ELSE SUBSTR(rootsourceid, 1, 4)
+         END AS rootsourceid_prefix
+        ,pagesource
+        ,CASE WHEN GET_JSON_OBJECT(extend,'$.rootsessionid') = subsessionid
+              THEN '首层' ELSE '裂变层'
+         END AS layer_type
+        ,COUNT(1) AS exp_cnt
+        ,COUNT(DISTINCT mid) AS dau
+FROM    loghubods.dwd_recsys_alg_exposure_base_20250108
+WHERE   dt = '${dt}'
+AND     apptype IN ('0','4')
+AND     page IN ("回流后沉浸页&内页feed","详情后沉浸页","首页feed","详情页","回流页","其他")
+GROUP BY apptype
+         ,CASE WHEN rootsourceid = '' OR rootsourceid IS NULL THEN '内部'
+               ELSE SUBSTR(rootsourceid, 1, 4)
+          END
+         ,pagesource
+         ,CASE WHEN GET_JSON_OBJECT(extend,'$.rootsessionid') = subsessionid
+               THEN '首层' ELSE '裂变层'
+          END
+;

tasks/00_尾号实验/探查_渠道lift.sql

@@ -0,0 +1,48 @@
+-- 按渠道（rootsourceid 前 4 位）拆 01 实验桶 vs 89 对照桶的 lift
+-- 只看"推荐"page，不分首层/裂变层（先简化）
+-- 跑法：python fetch_daily.py tasks/00_尾号实验/探查_渠道lift.sql --start 20260404 --end 20260415 --force
+--
+-- 验证假设：
+--   1. 产品 4 的主渠道 dyyj 在异常期 cn_rov 稳/涨
+--   2. 产品 0 的主渠道 toul/dyyq 在异常期 cn_rov 跌
+--   3. 两个产品在 dyyj 渠道的响应应该一致（同样渠道同样反应）
+
+SELECT  dt
+        ,apptype
+        ,CASE WHEN SUBSTR(GET_JSON_OBJECT(extend,'$.rootsessionid'),
+                          LENGTH(GET_JSON_OBJECT(extend,'$.rootsessionid')),1) IN ('0','1')
+              THEN '01'
+              WHEN SUBSTR(GET_JSON_OBJECT(extend,'$.rootsessionid'),
+                          LENGTH(GET_JSON_OBJECT(extend,'$.rootsessionid')),1) IN ('8','9')
+              THEN '89'
+              ELSE 'other'
+         END AS suffix_group
+        ,CASE WHEN rootsourceid = '' OR rootsourceid IS NULL THEN '内部'
+              ELSE SUBSTR(rootsourceid, 1, 4)
+         END AS channel
+        ,COUNT(1) AS exp
+        ,COUNT(DISTINCT mid) AS dau
+        ,SUM(return_n_uv) AS return_n_uv
+        ,SUM(is_share) AS is_share
+        ,SUM(share_cnt) AS share_cnt
+        ,COALESCE(SUM(return_n_uv) / COUNT(1), 0) AS bn_rov
+FROM    loghubods.dwd_recsys_alg_exposure_base_20250108
+WHERE   dt = '${dt}'
+AND     apptype IN ('0','4')
+AND     page IN ("回流后沉浸页&内页feed","详情后沉浸页","首页feed","详情页")  -- 推荐 page
+AND     SUBSTR(GET_JSON_OBJECT(extend,'$.rootsessionid'),
+               LENGTH(GET_JSON_OBJECT(extend,'$.rootsessionid')),1) IN ('0','1','8','9')
+GROUP BY dt
+         ,apptype
+         ,CASE WHEN SUBSTR(GET_JSON_OBJECT(extend,'$.rootsessionid'),
+                           LENGTH(GET_JSON_OBJECT(extend,'$.rootsessionid')),1) IN ('0','1')
+               THEN '01'
+               WHEN SUBSTR(GET_JSON_OBJECT(extend,'$.rootsessionid'),
+                           LENGTH(GET_JSON_OBJECT(extend,'$.rootsessionid')),1) IN ('8','9')
+               THEN '89'
+               ELSE 'other'
+          END
+         ,CASE WHEN rootsourceid = '' OR rootsourceid IS NULL THEN '内部'
+               ELSE SUBSTR(rootsourceid, 1, 4)
+          END
+;

tasks/00_尾号实验/探查_重复推荐率.sql

@@ -0,0 +1,35 @@
+-- 验证假设：异常期推给用户的视频，是否有更高比例是"用户过去 7 天已经看过"的？
+-- 跑法：python fetch_daily.py tasks/00_尾号实验/探查_重复推荐率.sql --start 20260408 --end 20260415 --force
+--
+-- 字段：
+--   apptype: 0 / 4
+--   total_exp: 当天该 apptype 的总曝光数（推荐页）
+--   repeat_exp: 其中 (mid, vid) 在过去 7 天该 mid 已看过的曝光数
+--   repeat_pct: repeat_exp / total_exp
+--   unique_users / unique_vids: 触达用户/视频数
+
+SELECT  c.apptype
+        ,COUNT(1) AS total_exp
+        ,SUM(CASE WHEN h.mid IS NOT NULL THEN 1 ELSE 0 END) AS repeat_exp
+        ,COUNT(DISTINCT c.mid) AS unique_users
+        ,COUNT(DISTINCT c.vid) AS unique_vids
+FROM    (
+            -- 当天推给用户的曝光（推荐页）
+            SELECT apptype, mid, vid
+            FROM   loghubods.dwd_recsys_alg_exposure_base_20250108
+            WHERE  dt = '${dt}'
+            AND    apptype IN ('0', '4')
+            AND    page IN ("回流后沉浸页&内页feed","详情后沉浸页","首页feed","详情页")
+        ) c
+LEFT JOIN (
+            -- 过去 7 天该用户看过的所有 (mid, vid)（不限页面）
+            SELECT DISTINCT mid, vid
+            FROM   loghubods.dwd_recsys_alg_exposure_base_20250108
+            WHERE  dt < '${dt}'
+            AND    dt >= TO_CHAR(DATEADD(TO_DATE('${dt}', 'yyyymmdd'), -7, 'dd'), 'yyyymmdd')
+            AND    apptype IN ('0', '4')
+        ) h
+ON      c.mid = h.mid
+AND     c.vid = h.vid
+GROUP BY c.apptype
+;

tasks/00_尾号实验/模型预估诊断_v1.sql

@@ -0,0 +1,211 @@
+-- ════════════════════════════════════════════════════════════════════════════
+-- 模型预估诊断 v1：按天 × 策略，分析 str / ros 预估均值、COPC、负数占比
+--
+-- 目标：诊断线上 ros (NorXGBScore) 出现负数的问题
+--   - str / ros 预估均值（原始 + 经过 1.22*pow(x,1.15) 变换后）
+--   - COPC 校准度（actual / predicted）
+--   - ros 负数占比 (NorXGBScore < 0)
+--   - 极值诊断（min/max）
+--
+-- 字段含义：
+--   - str_pred    = scoresMap.fmRov            (XGB str 预测)
+--   - ros_pred    = scoresMap.NorXGBScore     (XGB ros 原始预测，可能为负)
+--   - ros_pred_tx = 1.22 * pow(NorXGBScore, 1.15)  (线上变换后，负数 → NULL)
+--
+-- 数据源：loghubods.dwd_recsys_alg_sample_all_20250212
+-- 分组：dt × apptype × abcode (策略, 通过尾号→策略映射)
+-- ════════════════════════════════════════════════════════════════════════════
+WITH t_suffix_group AS
+(
+    SELECT "a" AS suffix, "ab" AS suffix_group
+    UNION ALL SELECT "b", "ab"
+    UNION ALL SELECT "0", "01"
+    UNION ALL SELECT "1", "01"
+    UNION ALL SELECT "2", "2c"
+    UNION ALL SELECT "c", "2c"
+    UNION ALL SELECT "3", "34"
+    UNION ALL SELECT "4", "34"
+    UNION ALL SELECT "5", "5d"
+    UNION ALL SELECT "d", "5d"
+    UNION ALL SELECT "6", "67"
+    UNION ALL SELECT "7", "67"
+    UNION ALL SELECT "8", "89"
+    UNION ALL SELECT "9", "89"
+    UNION ALL SELECT "e", "ef"
+    UNION ALL SELECT "f", "ef"
+)
+,t_experiment_map AS
+(
+    -- ── apptype = 4 ──────────────────────────────────────────────────
+    SELECT "4" AS apptype, "ab" AS suffix_group, "实验组：变更str*ros建模目标实验 有问题" AS abcode, "20260413" AS start_dt, "20260415" AS end_dt
+    UNION ALL SELECT "4", "ab", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
+    UNION ALL SELECT "4", "01", "实验组：变更str*ros建模目标实验", "20260320", "20260410"
+    UNION ALL SELECT "4", "01", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "4", "01", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
+    UNION ALL SELECT "4", "67", "实验组：变更str*ros建模目标实验", "20260330", "20260410"
+    UNION ALL SELECT "4", "67", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "4", "67", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
+    UNION ALL SELECT "4", "5d", "实验组：变更str*ros建模目标实验", "20260407", "20260410"
+    UNION ALL SELECT "4", "5d", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "4", "5d", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
+    UNION ALL SELECT "4", "34", "实验组：变更str*ros建模目标实验", "20260407", "20260410"
+    UNION ALL SELECT "4", "34", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "4", "34", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
+    UNION ALL SELECT "4", "67", "实验组：bn_ros新损失函数",        "20260311", "20260319"
+    UNION ALL SELECT "4", "5d", "实验组：解构特征排序str模型",     "20260314", "20260406"
+    UNION ALL SELECT "4", "ef", "实验组：解构特征排序str模型&召回", "20260314", "20260320"
+    UNION ALL SELECT "4", "ef", "实验组：DNN模型",                 "20260407", "29991231"
+    UNION ALL SELECT "4", "2c", "实验组：DNN模型-调参",            "20260413", "29991231"
+    UNION ALL SELECT "4", "89", "对照组",                          "20260301", "299991231"
+
+    -- ── apptype = 0 ──────────────────────────────────────────────────
+    UNION ALL SELECT "0", "ab", "实验组：变更str*ros建模目标实验 有问题", "20260413", "29991231"
+    UNION ALL SELECT "0", "ab", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "01", "实验组：变更str*ros建模目标实验", "20260320", "20260410"
+    UNION ALL SELECT "0", "01", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "0", "01", "实验组：变更str*ros建模目标实验", "20260416", "29991231"
+    UNION ALL SELECT "0", "34", "实验组：变更str*ros建模目标实验", "20260330", "20260410"
+    UNION ALL SELECT "0", "34", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "0", "34", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "67", "实验组：变更str*ros建模目标实验", "20260330", "20260410"
+    UNION ALL SELECT "0", "67", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "0", "67", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "5d", "实验组：变更str*ros建模目标实验", "20260407", "20260410"
+    UNION ALL SELECT "0", "5d", "实验组：变更str*ros建模目标实验 有问题", "20260411", "20260415"
+    UNION ALL SELECT "0", "5d", "实验组：DNN模型-调参", "20260416", "29991231"
+    UNION ALL SELECT "0", "ef", "实验组：DNN模型-调参",            "20260410", "29991231"
+    UNION ALL SELECT "0", "2c", "实验组：DNN模型",                 "20260413", "29991231"
+    UNION ALL SELECT "0", "89", "对照组",                          "20260301", "29991231"
+)
+-- 抽取模型分 & 尾号
+-- 关键字段：
+--   scoresMap.fmRov       = XGB str 预测（所有策略都有）
+--   scoresMap.NorXGBScore = XGB ros 原始预测（XGB 策略下有）
+--   scoresMap.NorDNNScore = DNN ros 原始预测（DNN 策略下有）
+-- 上线变换：1.22 * pow(x, 1.15)，x<0 → NULL
+,t_scores AS
+(
+    SELECT  dt
+            ,apptype
+            ,mid
+            ,vid
+            ,is_share
+            ,share_cnt
+            ,is_return_noself
+            ,return_n_uv
+            ,return_n_uv_noself
+            ,SUBSTR(GET_JSON_OBJECT(extend,'$.rootsessionid'),
+                    LENGTH(GET_JSON_OBJECT(extend,'$.rootsessionid')),1) AS suffix
+            -- 一次性抽出 scoresMap 字符串，避免重复 GET_JSON_OBJECT
+            ,REPLACE(GET_JSON_OBJECT(extend_alg,'$.scoresMap'),"\\","") AS scoresmap_clean
+    FROM    loghubods.dwd_recsys_alg_sample_all_20250212
+    WHERE   dt = '${dt}'
+    AND     apptype IN ("0","4")
+    AND     extend_alg IS NOT NULL
+)
+,t_scores2 AS
+(
+    SELECT  dt
+            ,apptype
+            ,mid, vid
+            ,is_share, share_cnt, is_return_noself, return_n_uv, return_n_uv_noself
+            ,suffix
+            -- str 预测
+            ,CAST(GET_JSON_OBJECT(scoresmap_clean,'$.fmRov') AS DOUBLE) AS str_pred
+            -- XGB ros 原始
+            ,CAST(GET_JSON_OBJECT(scoresmap_clean,'$.NorXGBScore') AS DOUBLE) AS xgb_ros_raw
+            -- DNN ros 原始
+            ,CAST(GET_JSON_OBJECT(scoresmap_clean,'$.NorDNNScore') AS DOUBLE) AS dnn_ros_raw
+    FROM    t_scores
+)
+-- 关联实验映射
+,t_base AS
+(
+    SELECT  s.*
+            ,sg.suffix_group
+            ,COALESCE(m.abcode,"对照组") AS abcode
+    FROM    t_scores2 s
+    INNER JOIN t_suffix_group sg ON s.suffix = sg.suffix
+    LEFT JOIN t_experiment_map m
+    ON      s.apptype = m.apptype
+    AND     sg.suffix_group = m.suffix_group
+    AND     '${dt}' BETWEEN m.start_dt AND m.end_dt
+)
+-- 按天 × 策略聚合
+,t_metrics AS
+(
+    SELECT  dt
+            ,apptype
+            ,abcode
+            -- ── 样本量 & 字段覆盖 ──
+            ,COUNT(1) AS exp_cnt
+            ,SUM(CASE WHEN str_pred IS NOT NULL THEN 1 ELSE 0 END) AS str_pred_cnt
+            ,SUM(CASE WHEN xgb_ros_raw IS NOT NULL THEN 1 ELSE 0 END) AS xgb_cnt
+            ,SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END) AS dnn_cnt
+
+            -- ── 真实值 ──
+            ,ROUND(SUM(is_share) / COUNT(1), 6) AS str_actual
+            ,ROUND(SUM(return_n_uv_noself) / NULLIF(SUM(is_return_noself),0), 6) AS ros_actual
+            ,ROUND(SUM(return_n_uv_noself) / COUNT(1), 6) AS rov_actual
+
+            -- ── 预估均值 ──
+            ,ROUND(AVG(str_pred), 6) AS str_pred_mean
+            ,ROUND(AVG(xgb_ros_raw), 6) AS xgb_ros_mean
+            ,ROUND(AVG(dnn_ros_raw), 6) AS dnn_ros_mean
+
+            -- ── COPC = actual / predicted ──
+            ,ROUND((SUM(is_share) / COUNT(1)) / NULLIF(AVG(str_pred),0), 4) AS str_copc
+            -- XGB ros COPC（在 XGB ros 非空 & 分享样本上）
+            ,ROUND(
+                AVG(CASE WHEN is_return_noself=1 THEN return_n_uv_noself END)
+                / NULLIF(AVG(CASE WHEN is_return_noself=1 THEN xgb_ros_raw END),0),
+                4) AS xgb_ros_copc
+            -- DNN ros COPC
+            ,ROUND(
+                AVG(CASE WHEN is_return_noself=1 THEN return_n_uv_noself END)
+                / NULLIF(AVG(CASE WHEN is_return_noself=1 THEN dnn_ros_raw END),0),
+                4) AS dnn_ros_copc
+
+            -- ── 负数占比（在该字段非空的样本中） ──
+            ,ROUND(SUM(CASE WHEN xgb_ros_raw < 0 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN xgb_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS xgb_neg_ratio
+            ,ROUND(SUM(CASE WHEN dnn_ros_raw < 0 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS dnn_neg_ratio
+            -- str 负数占比（sanity check）
+            ,ROUND(SUM(CASE WHEN str_pred < 0 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN str_pred IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS str_neg_ratio
+
+            -- ── 极值诊断 ──
+            ,ROUND(MIN(xgb_ros_raw), 6) AS xgb_ros_min
+            ,ROUND(MAX(xgb_ros_raw), 6) AS xgb_ros_max
+            ,ROUND(MIN(dnn_ros_raw), 6) AS dnn_ros_min
+            ,ROUND(MAX(dnn_ros_raw), 6) AS dnn_ros_max
+            ,ROUND(MIN(str_pred), 6) AS str_pred_min
+            ,ROUND(MAX(str_pred), 6) AS str_pred_max
+
+            -- ── DNN ros 分布桶（关注负数区间）──
+            ,ROUND(SUM(CASE WHEN dnn_ros_raw < -0.1 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS dnn_lt_neg01
+            ,ROUND(SUM(CASE WHEN dnn_ros_raw >= -0.1 AND dnn_ros_raw < 0 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS dnn_neg01_to_0
+            ,ROUND(SUM(CASE WHEN dnn_ros_raw >= 0 AND dnn_ros_raw < 0.5 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS dnn_0_to_05
+            ,ROUND(SUM(CASE WHEN dnn_ros_raw >= 0.5 AND dnn_ros_raw < 2 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS dnn_05_to_2
+            ,ROUND(SUM(CASE WHEN dnn_ros_raw >= 2 THEN 1 ELSE 0 END)
+                   / NULLIF(SUM(CASE WHEN dnn_ros_raw IS NOT NULL THEN 1 ELSE 0 END),0),
+                   6) AS dnn_gte_2
+    FROM    t_base
+    GROUP BY dt, apptype, abcode
+)
+SELECT  *
+FROM    t_metrics
+ORDER BY dt DESC, apptype, abcode
+;