现在有一个推荐场景的问题，
我的推荐预估的是 str、ros, vor 是统计出来的，最终的排序公式是str * ros * vor = vov
str用的是 fm 模型，ros用的是 xgb模型，vor 用的是 24 小时的统计量；
现在有一个问题，最近看到一些头部的 item，vov 低，但是给的曝光量很多，现在要你分析具体的原因；
我会给你一个 sql：
模型：
1. fmRov = str
1. fmRovOrigin = str采样还原前
2. NorXGBScore = ros 
3. vor=vor
真实
  1. Str = str-plus-noself
  2. Ros = ros-minus-noself
  3. Rov = return-n-uv-noself / exp
  4. Vov = new-exposure-cnt / exp

exp 是曝光的意思；具体 sql 如下，请你基于以下 sql 来分析具体低vov高曝光的原因是什么？这个问题的影响面有哪些？怎么解决：

WITH tab_base AS 
(
    SELECT  *
            ,((0.059 * fmRovOrigin) / (1 - (1 - 0.059) * fmRovOrigin)) AS online_fmrov
            ,((0.036 * fmRovOrigin) / (1 - (1 - 0.036) * fmRovOrigin)) AS real_fmrov
    FROM    (
                SELECT  dt
                        ,hh
                        ,vid
                        ,is_share
                        ,share_cnt
                        ,is_return_1
                        ,is_return_n
                        ,is_return_noself
                        ,return_1_uv
                        ,return_n_uv
                        ,return_n_uv_noself
                        ,new_exposure_cnt
                        ,CAST(score AS DOUBLE) AS score
                        ,CAST(GET_JSON_OBJECT(scoresmap,'$.fmRov') AS DOUBLE) AS fmRov
                        ,CAST(GET_JSON_OBJECT(scoresmap,'$.fmRovOrigin') AS DOUBLE) AS fmRovOrigin
                        ,CAST(GET_JSON_OBJECT(scoresmap,'$.NorXGBScore') AS DOUBLE) AS NorXGBScore
                        ,CAST(GET_JSON_OBJECT(scoresmap,'$.vor') AS DOUBLE) AS vor
                        ,CAST(GET_JSON_OBJECT(scoresmap,'$.hasReturnRovScore') AS DOUBLE) AS hasReturnRovScore
                FROM    (
                            SELECT  dt
                                    ,hh
                                    ,vid
                                    ,is_share
                                    ,share_cnt
                                    ,is_return_1
                                    ,is_return_n
                                    ,is_return_noself
                                    ,return_1_uv
                                    ,return_n_uv
                                    ,return_n_uv_noself
                                    ,new_exposure_cnt
                                    ,score
                                    ,REPLACE(GET_JSON_OBJECT(extend_alg,'$.scoresMap'),"\\","") AS scoresmap
                            FROM    loghubods.dwd_recsys_alg_sample_all_20250212
                            WHERE   dt BETWEEN '${start_dt}' AND '${end_dt}'
                            AND     hh BETWEEN '${start_hh}' AND '${end_hh}'
                            AND     apptype = '${apptype}'
                            --AND     vid IN ('62421458','55931081','62955809','58807530') 
                            AND     vid IN ('62967014','63159658','62151288')
                            AND     extend_alg IS NOT NULL
                            AND     GET_JSON_OBJECT(extend_alg,'$.scoresMap') IS NOT NULL
                            AND     page IN ("回流后沉浸页&内页feed","详情后沉浸页","首页feed","详情页")
                            AND     abcode IN ("ab0","ab1","ab2","ab3","ab4","ab5","ab6","ab7","ab8","ab9")
                            AND     abcode NOT IN ("ab100")
                        ) 
                WHERE   GET_JSON_OBJECT(scoresmap,'$.fmRov') IS NOT NULL
                AND     GET_JSON_OBJECT(scoresmap,'$.NorXGBScore') IS NOT NULL
                AND     GET_JSON_OBJECT(scoresmap,'$.vor') IS NOT NULL
                AND     GET_JSON_OBJECT(scoresmap,'$.hasReturnRovScore') IS NOT NULL
            ) 
)
,tab_pre AS 
(
    SELECT  dt --,hh
            ,vid
            ,COUNT(1) AS cnt
            ,AVG(score) AS score
            ,AVG(fmRov) AS fmRov
            ,AVG(online_fmrov) AS online_fmrov
            ,AVG(real_fmrov) AS real_fmrov
            ,AVG(1.22 * pow(NorXGBScore,1.15)) AS NorXGBScore
            ,AVG(vor) AS vor
            ,AVG(hasReturnRovScore) AS hasReturnRovScore
            ,STDDEV(score) AS std_score
            ,STDDEV(fmRov) AS std_fmRov
            ,STDDEV(NorXGBScore) AS std_NorXGBScore
            ,STDDEV(vor) AS std_vor
            ,STDDEV(hasReturnRovScore) AS std_hasReturnRovScore
    FROM    tab_base
    GROUP BY dt -- ,hh
             ,vid
)
,tab_post AS 
(
    SELECT  dt --,hh
            ,vid
            ,COUNT(1) AS exp
            ,round(COALESCE(SUM(is_share) / COUNT(1),0),6) AS str_one
            ,round(COALESCE(SUM(return_n_uv) / SUM(is_share),0),6) AS ros_one
            ,round(COALESCE(SUM(share_cnt) / COUNT(1),0),6) AS str
            ,round(COALESCE(SUM(return_n_uv) / SUM(share_cnt),0),6) AS ros
            ,round(COALESCE(SUM(is_return_1) / COUNT(1),0),6) AS str_plus
            ,round(COALESCE(SUM(return_n_uv) / SUM(is_return_1),0),6) AS ros_minus
            ,round(COALESCE(SUM(return_n_uv) / COUNT(1),0),6) AS rovn
            ,round(COALESCE(SUM(new_exposure_cnt) / COUNT(1),0),6) AS vovh24
            ,round(COALESCE(SUM(is_return_noself) / COUNT(1),0),6) AS str_plus_noself
            ,round(COALESCE(SUM(return_n_uv_noself) / SUM(is_return_noself),0),6) AS ros_minus_noself
    FROM    tab_base
    GROUP BY dt -- ,hh
             ,vid
)
SELECT  t1.*
        ,t2.*
FROM    tab_post t1
LEFT JOIN tab_pre t2
ON      t1.dt = t2.dt --AND     t1.hh = t2.hh
AND     t1.vid = t2.vid
ORDER BY t1.dt,t1.vid
;