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+version https://git-lfs.github.com/spec/v1
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diff --git a/tmp/proactive_publish_20260313/7593023927065038102_7593407584388795670/pub_7593407584388795670.mp4 b/tmp/proactive_publish_20260313/7593023927065038102_7593407584388795670/pub_7593407584388795670.mp4
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+version https://git-lfs.github.com/spec/v1
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diff --git a/tmp/proactive_publish_20260313/7602143673546984725_7604193599068146951/analysis.json b/tmp/proactive_publish_20260313/7602143673546984725_7604193599068146951/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..27a2679bd5a55558fa17e4f52c4c50c6978da531
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602143673546984725_7604193599068146951/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A female singer performs live on stage at a concert, with Spanish text overlay criticizing her performance.",
+  "投稿视频主题": "A group of four young women are shown in various settings (studio, stage, couch, dance studio) celebrating, practicing, and performing, with the same song playing and its lyrics overlaid.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature the exact same song. Video 1 shows a live performance of the song, while Video 2 uses the song as its central audio and narrative, depicting a group of aspiring performers' journey, directly inspired by the music.",
+  "model_error_analysis": "The ML model likely failed due to significant visual and contextual differences between the videos. Video 1 is a professional concert clip with critical text, while Video 2 is a narrative-driven piece about aspiring artists, featuring different settings (studio, dance room, empty theater) and using song lyrics as text. A model might struggle to connect these disparate visual scenes and text types, even with the shared audio, especially if the audio versions (live vs. studio/cover) have subtle differences that evade simple fingerprinting, or if the model prioritizes visual similarity too heavily over audio identity for 'causal' links."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602256064427330839_7603098072029138198/analysis.json b/tmp/proactive_publish_20260313/7602256064427330839_7603098072029138198/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..5ad674892316845d31552bc5a5543a9e528a79b2
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602256064427330839_7603098072029138198/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A customized grey Volkswagen T6 van is showcased, highlighting its modifications like bright green brake calipers, with text overlay 'It's just a slow van'.",
+  "投稿视频主题": "A 'good boy' persona is contrasted with night-time activities involving motorcycles and cars with friends, implying a rebellious or adventurous side, with text overlays 'Good Boy' rules and then 'Until the boys call'.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐"
+  ],
+  "reasoning": "Both videos utilize the exact same distinctive Russian rap music. The consumption video showcases a modified van, while the publish video uses the audio to narrate a 'good boy' persona transitioning to night-time vehicle activities with friends, suggesting a shared interest in vehicle culture. The shared audio is the primary causal link.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because its primary signal for similarity might be visual content or text, which are quite different between the two videos (a single van showcase vs. a narrative meme featuring a dog, motorcycles, and multiple cars). The model may not have a robust mechanism to identify strong causal links based solely on the reuse of a specific, non-globally trending audio track, especially when the visual themes, while broadly related to vehicle culture, are not identical in their specific subjects or presentation."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602270984690748694_7603038892320705814/analysis.json b/tmp/proactive_publish_20260313/7602270984690748694_7603038892320705814/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d608afc66b46898f5ce1c5b6b6e94cb117d08efa
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602270984690748694_7603038892320705814/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A woman holding a baby dances to a hip-hop song, turning to show her 'mum butt' in activewear, with text overlay referencing the song lyrics.",
+  "投稿视频主题": "A young girl, wearing a towel on her head, dances in front of a mirror, mimicking the actions of the 'mum butt' trend to the same hip-hop song, with text overlay calling her a 'mini me'.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos use the exact same trending audio, which features specific lyrics about identifying someone from their 'back' because 'it's heavy.' The second video's subject (a child) directly mimics the action of turning around to show their backside, playfully referencing the audio and the 'mum butt' concept from the first video (or the general trend). This indicates a direct causal relationship where the second video was inspired by the first's format and audio.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might prioritize visual content over the specific audio and the underlying meme/trend. While the audio is identical, the visual subjects (adult with baby vs. child alone) and settings are different. The model might not have recognized the specific 'mum butt' trend or the subtle behavioral mimicry (turning to show the backside) as a direct causal link, especially since the text overlays are also different, even though they both play on identity in relation to the audio. The model likely missed the strong signal from the exact audio match combined with the specific, mimicked action that defines the trend."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602366022103878929_7602669638551391496/analysis.json b/tmp/proactive_publish_20260313/7602366022103878929_7602669638551391496/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..11c59be721cb798c5348629425096b888eb0c97e
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602366022103878929_7602669638551391496/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A barber meticulously trims and shapes a man's beard and sideburns, showcasing the grooming process and the final clean look.",
+  "投稿视频主题": "A comedy skit where a client repeatedly sniffs and wipes his nose with the barber's cape, leading to the barber's frustration and eventually kicking the client out of the barbershop.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are set in a barbershop and feature a barber and a client. While one is a grooming demonstration and the other is a comedy skit, they both fall within the specific interest vertical of barbershop content.",
+  "model_error_analysis": "The ML model likely failed because it focused on the distinct primary content types (grooming demonstration vs. comedy skit) and the lack of shared audio or specific visual templates. It might have missed the fine-grained thematic connection based on the shared setting (barbershop) and character roles (barber, client), which requires a deeper semantic understanding of the context rather than just surface-level features."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602580322869366038_7602742455183707414/analysis.json b/tmp/proactive_publish_20260313/7602580322869366038_7602742455183707414/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..216f0c2c5a9a426939d73cb8204b23ab16ac9d7c
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602580322869366038_7602742455183707414/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "A person reviews 11 books they read in January, showcasing both physical books and e-books on a Kindle, with animated rose overlays.",
+  "投稿视频主题": "A woman reviews 11 books she read in January, holding up physical books against a bookshelf background and showing one e-book on an iPad.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos are 'January reading wrap-up' videos, a popular and recognizable content format in the BookTok community. They share the same background music, highly similar spoken phrases/text overlays (mentioning 'January reading wrap-up' and '11 books'), and the specific action of presenting and reviewing books one by one. Furthermore, they both feature the same book 'L'Impératrice Les Yakuzas'. These strong commonalities indicate a causal relationship.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship due to a combination of factors. It might not have recognized 'January reading wrap-up' as a specific, recurring content format or meme within the BookTok community, which requires cultural and domain-specific knowledge. The semantic similarity of spoken content (e.g., 'bilan lecture de janvier' and '11 livres') might have been missed if the model relies on exact keyword matching rather than semantic understanding. Additionally, while both videos show the same specific book ('L'Impératrice Les Yakuzas'), the model's object recognition might not be robust enough to identify it across different presentation styles (physical book vs. e-reader display) and varying visual contexts. The shared specific creative action of holding up and reviewing books one by one, a common template, might also be difficult for a model to identify as a '主体行为/形态' without explicit training on such content patterns."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602700620830625046_7602866165395803414/analysis.json b/tmp/proactive_publish_20260313/7602700620830625046_7602866165395803414/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..fe5f615c1e88de3500a789fa3e03b060a328e461
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602700620830625046_7602866165395803414/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "一个纹身男子在户外伴随着德语歌曲，通过焚烧纸张、手捧鲜花和阅读书籍等行为表达悲伤和失落的情绪。",
+  "投稿视频主题": "一位女士在镜头前对同一首德语歌曲进行对口型表演，并用面部表情表达情绪，视频带有烟雾滤镜。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "投稿视频是对消费视频中使用的同一首德语歌曲进行的对口型表演，这表明投稿视频直接受到了消费视频中音乐的启发和影响，属于最强的因果关系。",
+  "model_error_analysis": "ML模型可能因为视频的视觉内容差异巨大而未能识别出因果关系。消费视频是户外场景中人物的全身或半身表演，而投稿视频是室内近距离的对口型自拍。模型可能过度依赖视觉特征，而未能有效识别并匹配两个视频中完全相同的背景音乐作为核心的因果连接点，或者未能将“对口型”这一行为与特定音频进行强关联识别。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602708595221875986_7604355289906826504/analysis.json b/tmp/proactive_publish_20260313/7602708595221875986_7604355289906826504/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..affc591caa6debbbc62ab60c24bd541986387058
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602708595221875986_7604355289906826504/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "一个蹒跚学步的女孩和新生儿的对比，配以文字询问是否已开始为两岁生日派对做准备，新生儿则表现出困惑的表情，表达了时间飞逝的幽默感。",
+  "投稿视频主题": "一个婴儿从超声波到一岁生日的成长蒙太奇，展示了其不同阶段的照片，并以生日派对场景结束。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "消费视频展示了一个关于孩子成长速度和生日派对的流行梗，通过对比蹒跚学步的孩子和新生儿来表达时间飞逝的幽默感。投稿视频直接回应了这一主题，通过蒙太奇展示了婴儿从出生到一岁生日的成长过程，是该梗的直接演绎或回应。",
+  "model_error_analysis": "ML模型可能未能识别出这两个视频共享的特定育儿主题梗或病毒式玩法。模型可能侧重于表面差异，例如不同的背景音乐（情感歌曲与生日歌）、不同的具体文字内容（尽管核心情感一致），以及视频1中是蹒跚学步的孩子和新生儿，而视频2中是婴儿的成长过程。模型可能缺乏对这种特定文化语境下“时间飞逝，孩子成长太快”的育儿梗的深层语义理解，无法将投稿视频视为对消费视频所提出情境的直接回应或阐释。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602729554339253526_7603093834116943126/analysis.json b/tmp/proactive_publish_20260313/7602729554339253526_7603093834116943126/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..3a9700dd98f77867d87742a2c038430e9668aacf
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602729554339253526_7603093834116943126/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A man humorously expresses his emotional attachment to a black and white foster dog, implying he doesn't want to give her back, despite their original intention to foster multiple dogs.",
+  "投稿视频主题": "Two dogs, one black and white and one fluffy light-colored, are shown sleeping peacefully on a couch, set to the song 'You've Got a Friend in Me.'",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos center around the theme of loving dog companionship. The consumption video features a man's emotional bond with a black and white foster dog, while the publish video shows two dogs, including a black and white one very similar in appearance, sleeping peacefully to a song about friendship. The specific type of dog (black and white, Border Collie-like) is a strong visual link.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because it might not have recognized the specific breed/appearance of the black and white dog as a strong enough '拍摄对象' (subject of shooting) match, especially since the dogs are not identical and the primary actions differ (man talking/interacting with dog vs. dogs sleeping). The model might have focused on the different human presence or the different activities. It also likely missed the nuanced emotional theme of dog companionship conveyed through the man's ironic humor in the consumption video and reinforced by the song choice ('You've Got a Friend in Me') in the publish video, which requires a deeper semantic and cultural understanding."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602843396088106262_7602995295437278486/analysis.json b/tmp/proactive_publish_20260313/7602843396088106262_7602995295437278486/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..ef5144aa0e51071184b958619e751a959a12dda8
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602843396088106262_7602995295437278486/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A still image of a fluffy, light brown and dark brown cat with the name 'Oscar z' overlaid, accompanied by somber piano music.",
+  "投稿视频主题": "A grey kitten is shown drinking milk from a bowl, with text 'She really liked this' and a cheerful pop song playing.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature pet cats. The consumption video shows an adult cat, and the publish video shows a kitten drinking milk. They share the specific interest vertical of 'pet cats'.",
+  "model_error_analysis": "The ML model likely failed because the videos have completely different audio, text overlays, and visual presentation styles (still image vs. dynamic video, different cat breeds/ages). Without strong signals like shared audio or a specific visual template, the model might struggle to identify the fine-grained thematic similarity of 'pet cats' based solely on object recognition of different cats."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602915847211977992_7604398958395559186/analysis.json b/tmp/proactive_publish_20260313/7602915847211977992_7604398958395559186/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2e1bfb108faa285981d8b599c29010caa9ae982
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602915847211977992_7604398958395559186/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "A young man records himself using a TikTok filter that displays 'D De Diosa' and 'Únete a mi Club de fans' while speaking to the camera.",
+  "投稿视频主题": "The same young man participates in a multi-person live stream, still using the identical 'D De Diosa' TikTok filter.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "语句文案",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature the same user engaging with the exact same unique TikTok filter ('D De Diosa' and 'Únete a mi Club de fans'), which functions as a specific creative effect or meme, indicating a strong causal link.",
+  "model_error_analysis": "The ML model likely failed to recognize the specific TikTok filter as a unique and causally linking meme/special effect. It might have treated the filter as a generic visual overlay and been confused by the different video formats (solo vs. multi-person live stream), thus missing the strong thematic and behavioral connection. The Spanish text on the filter might also have been a barrier if the model lacks robust cross-lingual meme detection."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602946751540071701_7604027006077963528/analysis.json b/tmp/proactive_publish_20260313/7602946751540071701_7604027006077963528/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..1cc09a6646477d4d7564b4dc3f22b84f36311a66
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602946751540071701_7604027006077963528/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "一个自行车车轮在地面上快速旋转，产生大量烟雾，伴随着发动机轰鸣和轮胎摩擦的声音。",
+  "投稿视频主题": "一段蒙太奇视频，展示了一辆绿色电动自行车在不同户外和室内环境中的外观和细节。",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "两个视频都以自行车为主要拍摄对象。消费视频展示了自行车进行烧胎特技，而投稿视频则展示了一辆电动自行车的不同角度和场景，两者都属于自行车这一细分主题。",
+  "model_error_analysis": "ML模型可能主要关注了视频中的动态行为和音频特征。消费视频以剧烈的烧胎动作和发动机轰鸣声为主，而投稿视频则是一系列静态展示镜头配以舒缓音乐。这种行为和听觉上的巨大差异可能导致模型未能识别出两者在核心拍摄对象（自行车，尤其是这种特定风格的电动/改装自行车）上的细粒度主题相似性。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602984837502307606_7603479345079815446/analysis.json b/tmp/proactive_publish_20260313/7602984837502307606_7603479345079815446/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..8a0b215428d7f45855e2b3494c10a3b5621bb77d
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602984837502307606_7603479345079815446/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "该视频讲述了圣阿加莎的传说，包括她的殉道、她的面纱如何阻止埃特纳火山熔岩的奇迹，以及卡塔尼亚为纪念她而举行的现代游行。",
+  "投稿视频主题": "该视频展示了圣阿加莎雕像在华丽花车上的特写，花车装饰着粉色鲜花和灯光，伴随着宗教赞美诗。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "消费视频详细讲述了卡塔尼亚圣阿加莎的传说，包括她的殉道以及她如何成为卡塔尼亚对抗火山熔岩的守护神，并以现代纪念她的宗教游行结束。投稿视频则直接展示了该游行中圣阿加莎雕像的特写，这是消费视频中描绘的事件的核心元素。这种对同一特定宗教人物和事件的直接主题和视觉联系表明了强烈的因果关系。",
+  "model_error_analysis": "ML模型可能未能识别这种关系，因为它可能侧重于表面视觉特征而非深层语义。消费视频采用电影化的历史重演和AI生成视觉效果（如火山爆发），而投稿视频是真实事件的原始用户生成内容。两者在视觉风格上差异显著。此外，模型可能无法理解意大利语文本所传达的特定宗教叙事，也无法将消费视频中描绘的传说与投稿视频中展示的特定宗教偶像（圣阿加莎雕像）联系起来。音乐也不同，一个更偏向电影配乐，另一个是宗教赞美诗，这可能进一步误导了模型。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603022279718538516_7604021216944360712/analysis.json b/tmp/proactive_publish_20260313/7603022279718538516_7604021216944360712/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..109392b60e647bc36c8b14211320f525bdbcbedc
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603022279718538516_7604021216944360712/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A newborn baby is shown in a crib with parents performing a Hindu ritual (puja) for 'Day 6 Chaithi Puja', surrounded by fruits, a lit lamp, a letter board, and a 'Hello World' sign with birth details.",
+  "投稿视频主题": "A one-month-old baby is shown lying on a white blanket, surrounded by props for a milestone photoshoot, including a '1' balloon, a 'Hello World' sign with birth details, a letter board announcing 'I'M ONE MONTH OLD TODAY', and a baby onesie.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案",
+    "拍摄对象",
+    "画风呈现"
+  ],
+  "reasoning": "Both videos celebrate and document early baby milestones using a highly similar and recognizable social media format/template. This includes a baby lying down, a 'Hello World' sign with birth details, and a letter board announcing the specific milestone (Day 6 ritual vs. 1 month old photoshoot). The overall visual presentation and purpose are very similar, indicating a strong causal relationship where one likely inspired the other to use this popular content format.",
+  "model_error_analysis": "The ML model likely failed because it focused on surface-level differences rather than the underlying content template. Specific failure modes could include: 1) Different background music, which is a strong signal for many models. 2) Different specific text content on the letter boards ('Day 6 Chaithi Puja' vs. 'One Month Old Today'), despite the identical *format* of using a letter board for milestone announcements. 3) The 'Hello World' sign, while conceptually identical, might have different specific text (baby name, date) that a model might treat as dissimilar. 4) The model might not be trained to recognize this specific visual arrangement (baby + 'Hello World' sign + letter board) as a common, causal content template for baby milestones, instead seeing them as distinct events (religious ritual vs. photoshoot)."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603057662082731286_7603508048769993987/analysis.json b/tmp/proactive_publish_20260313/7603057662082731286_7603508048769993987/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..7477e2d03255cf540722902fe3470032fcf9dd90
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603057662082731286_7603508048769993987/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A horror-themed animated video providing survival rules for encountering various animatronic characters from the Five Nights at Freddy's (FNAF) universe.",
+  "投稿视频主题": "A gameplay video of a Roblox horror/mystery game, featuring a dark hallway and utilizing a viral 'Scooby Doo' meme audio.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos belong to the horror/survival gaming genre. The consumption video provides survival rules for the FNAF horror game, while the publish video showcases gameplay from a Roblox horror/mystery game. The use of the 'Scooby Doo' meme audio in the publish video is a specific viral format often associated with mystery/horror games, indicating a strong causal link to the broader horror game theme.",
+  "model_error_analysis": "The ML model likely failed to recognize the causal relationship due to its inability to connect different game IPs (FNAF vs. Roblox) within the same horror genre. It might not have understood the cultural context of the 'Scooby Doo' audio as a viral meme format specifically used in Roblox horror/mystery games, treating it as unrelated music. The visual differences between CGI animation and Roblox gameplay could also have hindered the model from identifying the shared thematic genre."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603072200341507329_7604142589331115280/analysis.json b/tmp/proactive_publish_20260313/7603072200341507329_7604142589331115280/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..432da0afc6c7cce82342fd1082939516d7757b10
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603072200341507329_7604142589331115280/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "A first-person perspective video from inside an ambulance, showing a paramedic in uniform and featuring a text overlay about finding purpose in helping strangers, set to a melancholic Spanish song.",
+  "投稿视频主题": "A first-person perspective video from inside an emergency vehicle driving on a highway, featuring the exact same text overlay and melancholic Spanish song as the consumption video.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "语句文案",
+    "拍摄对象"
+  ],
+  "reasoning": "The publish video directly reuses the exact same text overlay and background music from the consumption video. This combination constitutes a specific meme or viral format, indicating a strong causal relationship.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might not have accurately identified the exact match of both the text overlay (requiring robust OCR) and the specific background music. While the visual content is related to emergency services, it's not identical (one stationary inside an ambulance, one driving on a highway), which might have led a visually-biased model to miss the strong audio and text cues for direct inspiration."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603075574315158806_7603118367762910486/analysis.json b/tmp/proactive_publish_20260313/7603075574315158806_7603118367762910486/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..7bdb2a592c7322f67d984f2d50f9bf64d25abd27
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603075574315158806_7603118367762910486/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A young man plays an acoustic guitar and sings a song cover, with lyrics displayed as text overlays.",
+  "投稿视频主题": "A young person plays an acoustic guitar and sings a cover of 'Man I Need' by Olivia Dean, with lyrics displayed as text overlays.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "画风呈现",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature a person performing a song cover while playing an acoustic guitar. They share a similar visual presentation style with close-up shots and on-screen lyrics, indicating a fine-grained thematic similarity in music performance.",
+  "model_error_analysis": "The ML model likely failed because it primarily relies on exact audio matching (same song ID) or high textual similarity for lyrics. Since the two videos feature different songs and therefore different lyrics, the model would not detect a direct match. It would need to recognize the 'acoustic guitar cover with lyrics' as a distinct and similar activity/format, which requires more nuanced visual and contextual understanding beyond just audio or text content."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603079625559887125_7603753412768910612/analysis.json b/tmp/proactive_publish_20260313/7603079625559887125_7603753412768910612/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..510e2f65f8949857d073cef528e3b951f70b2699
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603079625559887125_7603753412768910612/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "一位产后23天的妈妈分享她为哺乳期准备的一日三餐和营养补充，包括早餐、午餐、下午茶和晚餐，并展示了她如何携带宝宝进食。",
+  "投稿视频主题": "一位孕妇展示她为即将出生的宝宝准备的药房用品，包括湿巾、婴儿沐浴露和洗发水，并讨论了她将在产房使用的物品。",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "两个视频都围绕着新手妈妈和婴儿护理的主题。消费视频展示了产后妈妈的日常饮食和营养补充，而投稿视频则展示了孕妇为宝宝准备的洗护用品。两者都属于育儿和母婴护理的细分主题。",
+  "model_error_analysis": "ML模型可能未能识别这种相似性，因为它可能过于关注视频中具体的行为和物品（如视频1中的“饮食”和“膳食准备”与视频2中的“产品展示”和“开箱”），而忽略了更深层次的、细粒度的“母婴护理”或“育儿准备”这一主题。模型可能将“食物”和“婴儿用品”视为不相关的类别，未能捕捉到两者都服务于新生儿和产妇护理这一共同目的。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603114436525870358_7603434420065848598/analysis.json b/tmp/proactive_publish_20260313/7603114436525870358_7603434420065848598/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..2e17f5e11495bcd950bc79658ef7f75b046963ae
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603114436525870358_7603434420065848598/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "一位戴着豹纹发带的女士在家里与一个孩子一起对口型唱歌，背景中还有一名男士。",
+  "投稿视频主题": "一位女士抱着婴儿在家里对口型唱歌。",
+  "主题相似": "抽象主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "两个视频都展示了一位女士与一个孩子（或婴儿）在家庭环境中以自拍形式对口型唱歌。虽然歌曲不同，但“女士与孩子”这一拍摄对象以及“对口型”这一行为构成了抽象的主题相似性。",
+  "model_error_analysis": "模型可能未能识别出视频中“女士与孩子”这一共同的拍摄对象，以及两者都是在家庭环境中进行的休闲自拍对口型视频。由于两段视频的背景音乐不同，模型可能过度依赖音频相似性来判断对口型视频的关联性，从而忽略了视觉上和内容形式上的抽象相似性。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603118709992967446_7603141944167976214/analysis.json b/tmp/proactive_publish_20260313/7603118709992967446_7603141944167976214/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a1cd6ff284cc0b80ce320dcba997cce9c8530183
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603118709992967446_7603141944167976214/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A brown dog is being trained to wait patiently for a treat held in a person's hand, with text indicating the dog is 'really trying'.",
+  "投稿视频主题": "A German Shepherd dog is lying on a rug, happily chewing on a pig's ear treat, with text overlays discussing the treat's cost-effectiveness.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature pet dogs interacting with treats. The consumption video shows a dog being trained with treats, while the publish video shows a dog enjoying a specific type of treat. This indicates a fine-grained thematic similarity within the 'pet dogs and treats' vertical.",
+  "model_error_analysis": "The ML model likely failed because it couldn't identify the fine-grained thematic connection between two different dogs performing different actions (training vs. eating) with different types of treats, and with distinct audio and text overlays. The model might be looking for more direct causal indicators like shared audio, specific visual templates, or identical challenges, rather than a broader semantic understanding of 'pet dogs and treats' as a related content vertical."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603138308822076692_7603806260097453332/analysis.json b/tmp/proactive_publish_20260313/7603138308822076692_7603806260097453332/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..3bcc164dc6c14d5a1a23849ff9916dd208e947fd
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603138308822076692_7603806260097453332/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A fan edit showcasing various clips of Lisa from Blackpink, set to emotional music with Portuguese text overlays expressing affection for her.",
+  "投稿视频主题": "A fan edit featuring romantic moments between two women from a Thai drama, using the same emotional music and similar visual effects with English text overlays.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐"
+  ],
+  "reasoning": "Both videos are fan edits that utilize the exact same background music and a highly similar visual editing style, including multiple short clips, text overlays, and a sparkling effect. The publish video appears to have adopted the audio and editing template from the consumption video to create a tribute for a different subject.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it may not have accurately identified the exact same background music being used in both videos. Additionally, while the subjects are different (a K-pop idol vs. a drama couple), the model might have missed the strong stylistic similarity in the 'fan edit' template, including the specific transitions, text overlay presentation, and sparkling visual effect, which indicates a direct inspiration rather than just a broad thematic match."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603146769148513566_7604566499847687445/analysis.json b/tmp/proactive_publish_20260313/7603146769148513566_7604566499847687445/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..68cc4395ff206cf777ec20ba47a00fde06c820ab
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603146769148513566_7604566499847687445/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A POV video from a soccer goalkeeper's perspective, showing them getting distracted by a Powerade bottle and missing a goal during a game.",
+  "投稿视频主题": "A video showing children playing street soccer, focusing on a goalkeeper making a save during the game.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are centered around the sport of soccer/football, specifically featuring goalkeepers and the act of playing in goal. Video 1 is a humorous, staged POV, while Video 2 is a recording of a live game, but they share the same specific interest vertical.",
+  "model_error_analysis": "The ML model likely failed because the videos lack direct superficial similarities like shared audio, text, or a specific visual template/meme. The connection is thematic, revolving around the niche of 'soccer goalkeeping'. A model might struggle to semantically understand that both videos feature a goalkeeper in a soccer context, especially given the different camera angles (POV vs. wider shot) and the humorous, staged nature of the consumption video versus the more documentary style of the publish video. It would need advanced object recognition (goalkeeper, goal, ball) and activity recognition (playing soccer, making a save) to link them effectively."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603165062764711186_7603407222311292181/analysis.json b/tmp/proactive_publish_20260313/7603165062764711186_7603407222311292181/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..b1c65d2fc179c1e948072d990a6d41a4a3abb89f
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603165062764711186_7603407222311292181/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A young person wearing a homemade animal mask talks about creating a community or 'house' for therians and LGBTQ+ individuals, explaining rules and inviting participation.",
+  "投稿视频主题": "Multiple young people wearing elaborate animal masks (therian masks/fursuits) dance and pose, acting like animals in various settings, with a text overlay about not conforming to standards.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos are centered around the 'therian' subculture. The consumption video discusses creating a community for therians, while the publish video showcases individuals participating in this subculture by wearing animal masks and acting like animals. The consumption video's explicit discussion of the therian community could directly inspire the creation of content like the publish video, demonstrating participation in that community.",
+  "model_error_analysis": "The ML model likely failed due to its inability to recognize the specific niche 'therian' subculture as a strong causal link. The visual styles are quite different (homemade mask and casual selfie vs. elaborate fursuits and a more produced montage). There is no shared audio or identical text. The connection relies on understanding the specific cultural context and the thematic link between discussing a community and showcasing participation in it, which requires more than surface-level visual or audio feature matching."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603185260158881045_7603447262575906068/analysis.json b/tmp/proactive_publish_20260313/7603185260158881045_7603447262575906068/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..7ac7cfdc13063db879e64a3dd99685094e62554a
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603185260158881045_7603447262575906068/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A horror story about a monstrous creature (Yeti/Wendigo) in snowy mountains, featuring AI-generated visuals and narration in Portuguese.",
+  "投稿视频主题": "A horror story about mermaids in the Bermuda Triangle, presented as a set of survival rules, featuring AI-generated visuals, narration, and meme reactions in Portuguese.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "画风呈现",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos are AI-generated horror/mystery stories about mythical creatures/legends, using a similar visual aesthetic (AI-generated eerie imagery) and narrative presentation style (text overlays, suspenseful atmosphere, storytelling format).",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it focused on the specific subjects (Yeti vs. Mermaids, snowy mountains vs. ocean) rather than the overarching creative format and genre. Both videos utilize a distinct AI-generated visual style for horror storytelling, combined with text overlays and a narrative structure, which represents a specific content trend. The inclusion of meme reaction images in the publish video might have further diversified its content, making it harder for a model to link it to the consumption video's more straightforward AI-generated horror narrative."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603389036920704264_7604264676964207892/analysis.json b/tmp/proactive_publish_20260313/7603389036920704264_7604264676964207892/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d55fcd5b5a75b70713202c09996175bdcbe2eab2
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603389036920704264_7604264676964207892/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A male streamer reacts excitedly to a hockey game (Canadiens vs Jets) displayed in a split-screen format, celebrating a goal.",
+  "投稿视频主题": "A male streamer reacts with surprise and exclamations to a video game (Rainbow Six Siege) displayed in a split-screen format, with game statistics and character selection also shown.",
+  "主题相似": "抽象主题相似",
+  "相似元素": [
+    "画风呈现",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos are 'streamer reaction' content, featuring a male streamer reacting to on-screen media. They share a very similar visual presentation style, using a split-screen layout where the streamer's face is at the top and the content they are reacting to is at the bottom. The core action of 'reacting to a screen' is also shared, indicating a thematic connection in content creation style, even if the specific media (hockey vs. video game) differs.",
+  "model_error_analysis": "The ML model likely failed because it focused too heavily on the specific content being reacted to (hockey vs. video game) rather than recognizing the shared 'streamer reaction video' format and visual template. It probably classified video 1 as 'sports' and video 2 as 'gaming,' missing the overarching abstract theme of 'reaction content' and the strong visual similarity in the split-screen presentation style, which is a key indicator of inspiration for this type of user-generated content."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603529071628225800_7604036865682951445/analysis.json b/tmp/proactive_publish_20260313/7603529071628225800_7604036865682951445/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..fadc0c64c317fb0c76d0e611eaae10e794683006
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603529071628225800_7604036865682951445/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A close-up view of various custom decorated pens featuring character charms and rhinestones, alongside bags of colorful beads and decorative charms.",
+  "投稿视频主题": "An outdoor market stall displaying a wide array of custom decorated pens, various beads and charms for crafting, decorated tumblers, and other handmade items.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos showcase the same specific niche craft: custom decorated pens made with beads and character charms. Video 1 focuses on the materials and some finished products, while Video 2 displays a market stall selling these exact types of items, indicating a strong fine-grained thematic connection within the crafting vertical.",
+  "model_error_analysis": "The ML model likely failed to detect this similarity because the visual presentation differs significantly (close-ups of materials vs. wide shots of a market stall). The music is also completely different. The model would need to understand the specific function and type of the craft items (custom beaded pens with character charms) rather than just generic object detection (e.g., 'pens', 'beads'), which requires a deeper semantic understanding of the niche craft."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603529734223383828_7604261847734275335/analysis.json b/tmp/proactive_publish_20260313/7603529734223383828_7604261847734275335/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a6fd3e9821d8b4f5dbd0f767ef449ff1c389f4a2
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603529734223383828_7604261847734275335/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A green dump truck navigates challenging, muddy, and unpaved rural roads during a rainy day, with the driver narrating the journey and showing a trick to clear the windshield.",
+  "投稿视频主题": "A white, customized International dump truck is showcased through various shots, driving on both paved and unpaved roads, set to a reggaeton song.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature dump trucks driving on various roads, including challenging rural and unpaved sections. The consumption video is a narrative vlog about a day's work in a dump truck, while the publish video showcases a customized dump truck in similar environments, indicating a shared specific interest in dump trucks and their operation.",
+  "model_error_analysis": "The ML model likely failed due to significant visual differences in the specific trucks (older green vs. customized white International) and completely different audio (narrative voiceover vs. reggaeton music). The model might not have recognized the fine-grained thematic similarity of 'dump trucks' and their associated driving context (rural, challenging roads) if it primarily relies on superficial visual or audio matches rather than deeper semantic understanding of vehicle type and activity."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603597531121011986_7604027676130594055/analysis.json b/tmp/proactive_publish_20260313/7603597531121011986_7604027676130594055/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..8d5536088d8c8cfda884b63bac79ea3ea0b4b308
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603597531121011986_7604027676130594055/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "一个健身教练在健身房指导一名女性进行坐姿高位下拉训练。",
+  "投稿视频主题": "一名男子在健身房进行哑铃推举训练，视频采用分屏形式，下半部分展示了一首在他脑海中循环的歌曲的演唱者。",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "两个视频都以健身房为背景，并展示了人们进行健身锻炼的场景。尽管视频类型不同（教学与健身梗），但它们都属于健身这一细粒度主题。",
+  "model_error_analysis": "ML模型可能未能识别出这两个视频的细粒度主题相似性，因为它可能过于关注视频的特定动作（高位下拉 vs 哑铃推举）和呈现形式（教学视频 vs 分屏梗图）。模型可能没有将健身房场景和健身活动作为足够强的共同特征来建立主题关联，尤其是在投稿视频中引入了与健身动作无关的流行歌曲演唱者作为视觉元素时，这可能进一步混淆了模型对核心主题的判断。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603814056583023893_7603967990312307975/analysis.json b/tmp/proactive_publish_20260313/7603814056583023893_7603967990312307975/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..387baa572784e934c7b5a62877e3abbd07aaca10
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603814056583023893_7603967990312307975/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "Two people are shoveling ice and slush in front of a Ford car dealership, with text humorously asking people to buy cars so they can afford a heated parking lot.",
+  "投稿视频主题": "A montage of a dark blue Ford F-350 Super Duty truck, showing it driving, its loud diesel engine, being worked on, and washed, with text highlighting 'Rowdy 6.4's'.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are thematically similar due to their explicit focus on the Ford brand and the automotive industry. Video 1 is set at a Ford dealership, and Video 2 features a specific Ford F-350 truck.",
+  "model_error_analysis": "The ML model likely failed to identify the fine-grained thematic similarity because it might not have effectively recognized and linked the 'Ford' brand across different contexts. Video 1 shows a Ford dealership sign and general Ford vehicles, while Video 2 focuses on a specific Ford F-350 truck. The model might have struggled to connect these visual cues as representing the same specific brand, especially since the activities (shoveling vs. truck maintenance/driving), audio, and text overlays are entirely different. It may have categorized them by broader themes like 'cars' or 'work' vs. 'trucks' and missed the underlying brand connection."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603818369183190303_7604234434702806280/analysis.json b/tmp/proactive_publish_20260313/7603818369183190303_7604234434702806280/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..3e10742aa552203b39d9fd74964c7286d5f137ab
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603818369183190303_7604234434702806280/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "一个纪念已故亲人的视频，以iPhone锁屏界面呈现，包含一条来自“叔叔”的短信，以及一首关于天堂的悲伤歌曲。",
+  "投稿视频主题": "一个关于悲剧性死亡（醉驾事故）的视频，通过模拟未接来电和短信界面来叙述，并配有一首表达精神困扰的歌曲。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "语句文案",
+    "主体行为/形态"
+  ],
+  "reasoning": "两个视频都采用了相似的创意模板，即通过模拟手机界面（锁屏/未接来电）和短信文本叠加来叙述一个关于悲剧性损失或对逝去亲人缅怀的故事。这种共享的叙事格式和主题强烈暗示了因果关系。",
+  "model_error_analysis": "ML模型可能未能识别出这种相似性，因为它可能过于关注低级特征，例如视频背景（墓地 vs 纯黑）、具体的文本内容（不同的死亡原因和信息）以及不同的背景音乐。模型可能难以抽象出这种特定的“手机界面+短信叙事+死亡/缅怀主题”的创意模板，这需要更深层次的语义理解和对流行叙事手法的文化知识。尽管音乐不同，但核心的视觉叙事模板和情感主题是高度一致的。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603852215660465416_7604220286849813781/analysis.json b/tmp/proactive_publish_20260313/7603852215660465416_7604220286849813781/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..dfe2bbe956f578b832bc489a448969547d00cb30
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603852215660465416_7604220286849813781/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A video showing an outdoor swimming pool with swimmers and palm trees, featuring text overlay announcing 'Swimmer's Day' and suggesting gifts like goggles and swimsuits.",
+  "投稿视频主题": "A video showing an outdoor swimming pool with a slide, featuring text overlay announcing 'Swimmer's Day' on February 12th and suggesting preparing swimming gear, while playing a song with lyrics about doing crazy things.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos explicitly announce 'Swimmer's Day' ('Dia del Nadador') and feature an outdoor swimming pool. The text overlays in both videos are highly similar, mentioning the upcoming day and suggesting preparation of swimming equipment, indicating a direct inspiration or participation in a shared trend/meme related to this specific event.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it may not have accurately parsed and understood the semantic meaning of the Spanish text overlays ('se viene el dia del nadador' and the subsequent suggestions for swimming gear) which are the primary indicators of the shared specific theme and meme. While both videos feature swimming pools, their visual characteristics are distinct (one a competitive pool by the sea, the other a recreational pool), and the audio is different, which might have led a model relying on visual and audio cues to miss the strong textual and thematic connection."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603876731857931540_7604241667603893524/analysis.json b/tmp/proactive_publish_20260313/7603876731857931540_7604241667603893524/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..27cce67d67eacdb5cad58aefdb8f090b32222539
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603876731857931540_7604241667603893524/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A fan edit featuring various clips of Mike Wheeler from 'Stranger Things' with a Funko Pop figure of the character superimposed.",
+  "投稿视频主题": "A fan edit showcasing a collection of aesthetic images and clips associated with the character Robin Buckley from 'Stranger Things'.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "语句文案",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are fan edits dedicated to characters from the same popular IP, 'Stranger Things'. They utilize a similar creative format or '玩法' within the fandom: compiling short, often aesthetic, clips or images set to music, with text overlays identifying the character, serving as a character tribute.",
+  "model_error_analysis": "The ML model likely failed to identify the causal relationship because it may not have recognized the shared 'Stranger Things' IP as the core connection. It might have focused on superficial differences such as the specific characters featured (Mike Wheeler vs. Robin Buckley), the distinct visual elements (Funko Pop vs. various aesthetic items), and the different background music. The model would need a deeper understanding of pop culture references and fan-edit genres to recognize that both videos adhere to a common 'character tribute' format for the same franchise, which is a strong indicator of a causal relationship in this context."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603884493329550609_7604041815758490901/analysis.json b/tmp/proactive_publish_20260313/7603884493329550609_7604041815758490901/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a6866796cf61bc555f0c3577680b5afe833c1821
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603884493329550609_7604041815758490901/analysis.json
@@ -0,0 +1,14 @@
+{
+  "消费视频主题": "一个粉色主题的ASMR史莱姆视频，背景是小马宝莉角色，配有关于雪豹的“热门观点”的画外音和文字。",
+  "投稿视频主题": "一个白色背景的ASMR史莱姆声音视频，背景是小马宝莉角色，配有关于“抱怨者”的画外音和文字，并为没有史莱姆背景而道歉。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "语句文案",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "投稿视频明显模仿了消费视频的特定创作模板，包括使用小马宝莉角色、ASMR史莱姆声音和以画外音及文字形式呈现的“抱怨”内容。投稿视频甚至在文案中明确提及“抱歉没有史莱姆背景”，直接呼应了消费视频的视觉风格，表明其受到了消费视频的启发。",
+  "model_error_analysis": "ML模型可能未能识别出这种特定的“抱怨+小马宝莉+ASMR史莱姆”组合作为一种病毒式模板或玩法。模型可能将小马宝莉角色视为不同的IP（尽管它们属于同一系列），或者将ASMR声音和文字内容视为独立元素，而没有理解它们共同构成了一个可复制的创作格式。此外，模型可能无法理解投稿视频中“抱歉没有史莱姆背景”这种文本对消费视频风格的直接引用，这需要更深层次的语义理解和上下文关联能力。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603902943246503175_7604332451615247623/analysis.json b/tmp/proactive_publish_20260313/7603902943246503175_7604332451615247623/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..f0e8a77ae7e055698c26da58328c490ed3ca7fdb
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603902943246503175_7604332451615247623/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A woman in a sparkly blue skeleton costume with a star crown and sunglasses dances and lipsyncs to a lively Spanish song in a party setting.",
+  "投稿视频主题": "A young woman with vibrant neon eye makeup and a colorful flower lei records a selfie video, lipsyncing to the same lively Spanish song.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature individuals lipsyncing to the identical background music, indicating a direct causal relationship where the consumption video's audio likely inspired the publish video. The specific action of lipsyncing to the same song is a strong indicator of causation.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because it might lack robust audio fingerprinting or cross-modal (audio-visual) understanding to recognize the exact same song being used for lipsyncing across two visually distinct videos. The visual content (different costumes, makeup, settings, and people) is very different, which could mislead a vision-centric model. The key causal feature here is the shared audio and the lipsyncing action, which requires strong audio analysis and action recognition capabilities."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603921933381455125_7604079730609982741/analysis.json b/tmp/proactive_publish_20260313/7603921933381455125_7604079730609982741/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..9d5131b2f0eefa0b7d9299b8f9245fa36a3d35bb
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603921933381455125_7604079730609982741/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A woman receives a surprise gift of roses and chocolates from her partner, celebrating Rose Day and showing affection.",
+  "投稿视频主题": "A couple and their young child enjoy a family outing at the beach, walking in the water and showing affection.",
+  "主题相似": "抽象主题相似",
+  "相似元素": [
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos depict a couple expressing love and affection within their relationship, with the first video focusing on a romantic surprise and the second on a family outing. The core theme of a loving relationship is shared, despite different specific contexts and activities.",
+  "model_error_analysis": "The ML model likely failed because it focused on superficial differences rather than the underlying abstract theme. The specific objects (roses, chocolates vs. beach, water), settings (indoor vs. outdoor), and events (Rose Day vs. family outing) are distinct. The model might not have recognized the shared 'couple' identity or the generalized 'showing affection' behavior across these different contexts, especially without shared audio or text overlays as strong signals."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603932047878442257_7603978976616336661/analysis.json b/tmp/proactive_publish_20260313/7603932047878442257_7603978976616336661/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..6fdc15e9ca98a0e5e91d84010a1b251b706e1e9b
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603932047878442257_7603978976616336661/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A night drive scene showing a car's dashboard with a text overlay about listening to others' problems while drowning in one's own.",
+  "投稿视频主题": "A snowy parking lot at night with a building in the background and a text overlay about listening to others' problems while drowning on one's own.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "Both videos use the exact same background music and feature a nearly identical, specific text overlay, indicating a direct inspiration from a viral format or meme.",
+  "model_error_analysis": "The ML model likely failed because the visual content of the two videos is distinctly different (car interior vs. outdoor parking lot). The model might not have adequately prioritized or detected the exact same background music and the highly similar, specific text overlay as strong causal signals, potentially focusing too much on visual scene similarity."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603947476332186901_7604063261130034433/analysis.json b/tmp/proactive_publish_20260313/7603947476332186901_7604063261130034433/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..ec2f8f049c60d05f14fd629165d2df3a6cc334f3
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603947476332186901_7604063261130034433/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "An animated speed drawing of the Danganronpa character Kokichi Ouma, showcasing his design and expressions.",
+  "投稿视频主题": "A fan art slideshow featuring Danganronpa characters Kokichi Ouma and Shuichi Saihara, set to the same background music.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature characters from the Danganronpa franchise and use the exact same background music. The consumption video is an animated drawing of a Danganronpa character, and the publish video is a fan art edit of Danganronpa characters, strongly suggesting the consumption video's music and IP content inspired the publish video.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might not have recognized the specific Danganronpa IP across different visual styles (animated drawing vs. fan art/manga panels). While the music is identical, the model might not prioritize audio similarity enough when the visual content's presentation style (drawing process vs. image slideshow) differs significantly, or it may lack the granular understanding of niche anime/game characters to link them effectively."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603977624448175368_7604464746045230354/analysis.json b/tmp/proactive_publish_20260313/7603977624448175368_7604464746045230354/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..0438f757d0cea1a997f2fd3a85be338416e8e102
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603977624448175368_7604464746045230354/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A cinematic travel video showcasing various landmarks and cityscapes of Albania, including its capital Tirana, set to an upbeat electronic song.",
+  "投稿视频主题": "A black and white, glitchy video featuring historical figures and national symbols of Albania and Kosovo, using the exact same electronic song.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos utilize the exact same background music, which is a strong indicator of a causal relationship on TikTok. Additionally, both videos center around the theme of Albania, with the consumption video showcasing its geography and the publish video its history and national identity.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship due to the significant visual disparity between the two videos. The consumption video is a colorful, modern travel montage, while the publish video is a black-and-white, glitchy historical/political montage. A model heavily reliant on visual features and style might not recognize the shared audio track or the overarching high-level theme of 'Albania' across such different visual presentations. The primary failure is likely the lack of robust audio fingerprinting or cross-modal understanding to connect the identical music in visually distinct contexts."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603979300127214866_7604577411136621844/analysis.json b/tmp/proactive_publish_20260313/7603979300127214866_7604577411136621844/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..fb0ea812bde74b46ed1ad3141e40cec1dc1dcd30
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603979300127214866_7604577411136621844/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "视频展示了一位演奏者在数字钢琴上弹奏带有宗教歌词的音乐，歌词以黄色字体叠加在屏幕上。",
+  "投稿视频主题": "视频展示了一位演奏者在数字钢琴上伴奏，一位歌手演唱《主祷文》，歌词以白色字体叠加在屏幕上，背景是教堂排练场景。",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "画风呈现",
+    "语句文案",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "两个视频都展示了在数字钢琴上演奏宗教音乐，并配有歌词叠加。尽管歌曲和具体歌词不同，但主题（宗教音乐演奏）、乐器（数字钢琴）、行为（弹奏和歌唱/展示歌词）以及歌词的呈现方式（屏幕叠加）都高度相似，属于同一细分兴趣领域。",
+  "model_error_analysis": "模型可能未能识别出这种细粒度的主题相似性，因为它可能过于依赖精确的音频匹配或文本内容匹配。尽管两个视频的音乐旋律和具体歌词不同，但它们都属于“数字钢琴演奏宗教歌曲并配有歌词”这一特定内容类型。模型可能将不同的歌曲和不同的拍摄环境（家庭 vs 教堂）视为不相关的信号，而忽略了核心的音乐类型、乐器和内容呈现方式的相似性。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7603993350802394389_7604087376469642517/analysis.json b/tmp/proactive_publish_20260313/7603993350802394389_7604087376469642517/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..f48ffa98954804494a061427546f9886bc8e915b
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7603993350802394389_7604087376469642517/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A person holds a bouquet of yellow roses in a store, with text overlay about buying flowers for oneself.",
+  "投稿视频主题": "A close-up shot of a bouquet of orange roses, accompanied by heart emojis.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos prominently feature bouquets of roses as their main subject, presented in a similar close-up, handheld style, indicating a shared specific interest in showcasing flowers.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because it might not have a fine-grained understanding of 'bouquets of roses' as a specific shared subject. The videos have different music, text overlays, and specific rose colors (yellow vs. orange), which could lead a model to focus on these superficial differences rather than the core commonality of the object being filmed and its presentation style. The connection is thematic and visual, which can be harder for models to pick up without explicit training on such object-level similarity, especially without shared audio or specific visual templates."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604019342124043540_7604368885785070868/analysis.json b/tmp/proactive_publish_20260313/7604019342124043540_7604368885785070868/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..79adc0cff6d524866b61410ddda83f5fc24a981d
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604019342124043540_7604368885785070868/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "一个AI生成的Bratz风格娃娃角色在哥特式背景下，伴随音乐和文字叠加进行表演。",
+  "投稿视频主题": "一个AI生成的赛车手形象的虚拟角色在车库背景下，伴随音乐跳舞并与头盔互动。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "两个视频都采用了AI生成虚拟角色进行表演的流行玩法/格式。尽管具体的角色形象、背景和音乐不同，但这种“AI虚拟角色表演”本身是一种可识别的创作模式，用户观看后可能受到启发，创作了同类型但内容不同的视频。",
+  "model_error_analysis": "ML模型可能未能识别这种因果关系，因为它可能过于关注具体的视觉元素（如角色外观、服装、背景）、音频和文本的直接匹配。然而，这两个视频的相似性在于它们都属于“AI生成虚拟角色表演”这一特定的TikTok内容创作趋势或玩法。模型可能缺乏对这种抽象的、基于创作模式的“玩法”相似性的理解，而将其视为两个视觉和听觉上完全不同的视频。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604023995578453256_7604406022966463752/analysis.json b/tmp/proactive_publish_20260313/7604023995578453256_7604406022966463752/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..5ae7ec2939680acfcb65638fa53a200519a00979
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604023995578453256_7604406022966463752/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "A compilation of clips showing people enjoying themselves at an outdoor music festival, with a text overlay 'Laneway is a Feeling'.",
+  "投稿视频主题": "A live performance by a female singer on an elaborate, gothic-themed stage, singing to an audience.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [],
+  "reasoning": "Both videos depict live music events. The consumption video shows the audience experience at a music festival, while the publish video shows a live performance by an artist at a concert. They share the fine-grained theme of live music/concerts.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to significant differences in low-level features. The audio tracks are completely different (generic festival music vs. a specific live song), and the visual styles contrast sharply (bright outdoor casual footage vs. dark indoor theatrical stage production). The model might not have the semantic understanding to connect 'music festival audience experience' with 'live concert performance' under the broader category of 'live music events' if it relies heavily on direct audio or visual matches, or specific keyword overlaps which are absent here."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604071937224199445_7604486246018075922/analysis.json b/tmp/proactive_publish_20260313/7604071937224199445_7604486246018075922/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..636230e2cc5da9330d44507685048f72d3c4bd92
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604071937224199445_7604486246018075922/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "Two young women are jogging outdoors in a park, with text overlay contrasting their healthy morning routine with others returning from partying.",
+  "投稿视频主题": "A group of young men are playing a casual game of football outdoors, with text overlay humorously contrasting their activity with a girlfriend's potential assumptions.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "语句文案"
+  ],
+  "reasoning": "Both videos utilize a popular 'POV' or contrasting narrative meme format, where the text describes an unexpected or alternative activity compared to a common assumption or another group's activity. This shared meme format, which acts as a template for content creation, indicates a causal relationship. Both also share a casual, handheld outdoor visual style.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it focused on the distinct physical activities (running vs. football) rather than the shared meme format conveyed through the text overlays. The model might not be equipped to understand the nuanced 'POV: expectation vs. reality' narrative structure as a viral template, which is a strong indicator of a causal link in social media content. It would require advanced text understanding and meme recognition capabilities to identify this type of thematic similarity."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604117742802701576_7604523788599938321/analysis.json b/tmp/proactive_publish_20260313/7604117742802701576_7604523788599938321/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..c56b73f6d53a6b2615d427239aa6f5bfddd59e08
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604117742802701576_7604523788599938321/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A husky dog is lying on a bed while a small Shih Tzu puppy barks at it from the floor.",
+  "投稿视频主题": "A German Shepherd dog is sleeping on a dog bed, making chewing motions as if dreaming about food.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature dogs as the main subject, falling into the 'pets' or 'dog content' category. However, the specific actions and scenarios (dog interaction vs. dog dreaming) are different, indicating a fine-grained thematic similarity rather than a direct causal link like a shared meme or challenge.",
+  "model_error_analysis": "The ML model likely failed because it did not detect a strong causal link such as shared audio, specific meme, or identical creative action. While both videos are about dogs, the specific activities are distinct. The model might be optimized for more direct forms of content reuse (e.g., same sound, same challenge) and thus missed the 'fine-grained thematic similarity' of 'pet/dog content' as a form of relatedness."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604119657179630856_7604130070600437010/analysis.json b/tmp/proactive_publish_20260313/7604119657179630856_7604130070600437010/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..57f9d1458396db2417b61c0daeffa4118f841a8a
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604119657179630856_7604130070600437010/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "Tucker Carlson interviews a guest about the biblical Nephilim, giant human bones, and a conspiracy theory alleging the Smithsonian suppressed evidence of their existence.",
+  "投稿视频主题": "An animated image of Jesus riding a camel in a desert, looking at a map, accompanied by a comedic audio clip about getting lost without Google Maps.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos engage with biblical narratives and figures. The consumption video discusses the Nephilim from Genesis, while the publish video features Jesus in a desert setting, indicating a shared thematic interest in biblical/religious content.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because there is no direct audio match, visual template reuse, or identical text. The connection is thematic, revolving around biblical figures and stories, which requires a deeper semantic understanding of the content rather than just surface-level feature matching. The model might not recognize 'Nephilim' and 'Jesus' as belonging to the same 'biblical figures' category, especially given the vastly different tones (serious discussion vs. comedic meme)."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604120387240234260_7604264832187108629/analysis.json b/tmp/proactive_publish_20260313/7604120387240234260_7604264832187108629/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..db25d4b904139d1387a457b9c87ac8bcd6e6c17c
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604120387240234260_7604264832187108629/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A man reviews a black 1985 Toyota Hilux SR5 Pickup model car, discussing its details, brand, and connection to 'Back to the Future'.",
+  "投稿视频主题": "A person reviews a neon green Porsche RWB model car, showcasing its details, brand, and limited edition status.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature a detailed review and showcase of a collectible die-cast model car. The presentation style, including holding the model, rotating it for various angles, and highlighting specific features and brands, is very similar, indicating a shared content format or '玩法' within the model car collecting niche.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it focused on the superficial differences between the two cars (a black Toyota pickup truck vs. a neon green Porsche sports car) rather than recognizing the highly specific and shared 'model car review' content format and presentation style. The model might not have understood that 'reviewing collectible die-cast cars' constitutes a distinct and recognizable content type or '玩法' that can inspire similar creations, especially when the visual and behavioral elements of the review are so consistent."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604133644516494613_7604325341783493906/analysis.json b/tmp/proactive_publish_20260313/7604133644516494613_7604325341783493906/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..0c51558871542327ae9a9849e3bbcb5f33ad0eb7
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604133644516494613_7604325341783493906/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A fluffy cat is shown sleeping in its bed, accompanied by a humorous Spanish voiceover from the cat's perspective, detailing its pampered life and expectations.",
+  "投稿视频主题": "A tabby cat is shown sleeping, presented with a dark, desaturated filter and melancholic English text overlays expressing emotional vulnerability and finding strength.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature a sleeping cat as their central subject. While the visual style, audio, and narrative tone are distinctly different (humorous and lighthearted in video 1, melancholic and artistic in video 2), the core fine-grained theme of 'sleeping cats' connects them.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to the significant differences in audio and visual style. Video 1 has a Spanish voiceover and a natural look, while Video 2 uses a melancholic English song, dark filters, and emotional text overlays. A model relying heavily on direct audio or visual feature matching would struggle to identify the shared core subject (a sleeping cat) when the presentation and mood are so divergent. It would need a more abstract understanding of the subject matter, independent of the creative execution."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604138193516055815_7604239035036437780/analysis.json b/tmp/proactive_publish_20260313/7604138193516055815_7604239035036437780/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..8ee5246bba5ec1b894fb7d8b3c0e44e6c0be43a3
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604138193516055815_7604239035036437780/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A young woman lipsyncs and dances to a song, transitioning from an indoor setting to an outdoor festival where she continues to dance.",
+  "投稿视频主题": "A live concert performance of the same song, viewed from the audience, with a text overlay identifying the artist as 'Malcolm Todd is Gold Coast's Sally'.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐"
+  ],
+  "reasoning": "Both videos feature the exact same song. Video 1 shows a person lipsyncing and dancing to the song, while Video 2 shows a live performance of the same song at a concert. The shared audio is a direct causal link.",
+  "model_error_analysis": "The ML model likely failed due to significant visual differences between the videos (casual selfie/festival vs. live concert footage). While the audio is identical, the acoustic properties might differ slightly due to live performance elements (crowd noise, live instrumentation) compared to a studio track, potentially reducing the model's confidence in audio similarity if not robustly handled. The model might prioritize visual context over the specific song identity as a causal factor."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604161389954862337_7604241413802380564/analysis.json b/tmp/proactive_publish_20260313/7604161389954862337_7604241413802380564/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..932124d194650185c00436835f21a93aad0dcefb
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604161389954862337_7604241413802380564/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A person prepares and packages mini pancakes (poffertjes) with various dipping sauces in a commercial setting.",
+  "投稿视频主题": "A slideshow showcasing various desserts from a cafe, including a rolled crepe, cheesecakes, a milkshake, and a dish of cut-up crepes/pancakes with dipping sauces.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "The consumption video focuses on making mini pancakes with multiple dipping sauces. The publish video, a dessert compilation, prominently features a dish of cut-up crepes/pancakes served with two dipping sauces, which is a very similar dessert concept and presentation style to the mini pancakes in the consumption video. Both fall within the specific interest vertical of pancake/crepe-based desserts with sauces.",
+  "model_error_analysis": "The ML model likely failed due to the visual differences in the specific form factor of the pancakes (mini round poffertjes vs. cut-up flat crepes) and the different contexts (preparation vs. finished display). Without a deeper semantic understanding of food categories and presentation styles, the model might not recognize these distinct visual representations as belonging to the same 'pancake/crepe dessert with dipping sauces' theme. There is no shared audio or identical visual template to aid the model."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604192834694040850_7604553253086383381/analysis.json b/tmp/proactive_publish_20260313/7604192834694040850_7604553253086383381/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..e2696b2acb8e4ce4bacefc717be07fa0a5bd4f66
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604192834694040850_7604553253086383381/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A young man in a Chivas jersey reports on the injury status of Chivas players Castillo and Romo, providing good news for Castillo and bad news for Romo.",
+  "投稿视频主题": "A man in a Chivas jersey performs a reaction meme, expressing happiness for Chivas victories but then sadness upon remembering that players Romo and Castillo got injured.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Video 1 reports on the specific injuries of Chivas players Romo and Castillo. Video 2 is a reaction meme that directly references these same players and their injuries ('Romo & Casti se lesionaron'), indicating a direct causal link where the news from Video 1 likely inspired the reaction in Video 2.",
+  "model_error_analysis": "The ML model likely failed to identify the causal relationship because it might not have performed robust named entity recognition (NER) and event linking across videos. It likely missed that 'Romo' and 'Castillo' (or 'Casti') refer to the same specific players and that 'lesionaron' (injured) refers to the same specific event in both videos. The model might have categorized both as general 'sports' or 'football' content but failed to detect the fine-grained thematic connection and the direct textual reference in the publish video to the specific news reported in the consumption video, especially given the different video formats (news report vs. reaction meme)."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7604198893898763541_7604200050855775508/analysis.json b/tmp/proactive_publish_20260313/7604198893898763541_7604200050855775508/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a2c68cb39ff8bb0de26d982e5a622923369692b6
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7604198893898763541_7604200050855775508/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A young woman in a black lace camisole lipsyncs to a Spanish song, performing a specific sequence of hand gestures and body movements.",
+  "投稿视频主题": "The same young woman in the same black lace camisole lipsyncs to a different Spanish song, performing the exact same sequence of hand gestures and body movements.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature the exact same person, in the same outfit and setting, performing the identical, specific sequence of hand gestures and body movements. This indicates a direct reuse of a creative performance template or choreography, even though the background music is different.",
+  "model_error_analysis": "The ML model likely failed because it primarily relies on audio similarity for lipsync videos to determine causal relationships. Since the background music is different in the two videos, the model would incorrectly classify them as unrelated. It might not be sophisticated enough to detect the identical, specific choreography and sequence of body movements as a 'template' or 'challenge' when the audio track has changed, despite the strong visual cues of the same person, outfit, and background."
+}
\ No newline at end of file