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diff --git a/tmp/proactive_publish_20260313/7582864625457384725_7592503137240386834/analysis.json b/tmp/proactive_publish_20260313/7582864625457384725_7592503137240386834/analysis.json
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+{
+  "消费视频主题": "A person hits a metal colander with a metal ladle, creating a rhythmic sound, while a voiceover repeatedly chants 'SYBAU FAITH'.",
+  "投稿视频主题": "A person hits a metal colander with a metal ladle, creating a rhythmic sound, while a voiceover repeatedly chants 'SYBAU 67'.",
+  "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": "Both videos replicate the exact same viral format or meme: hitting a metal colander with a metal ladle to create a rhythmic sound, accompanied by a voiceover chanting 'SYBAU [specific word/number]'. This indicates a direct causal relationship.",
+  "model_error_analysis": "The ML model likely failed to recognize this as a causal relationship because it might not have identified the specific 'colander hitting' action as a viral meme. While the objects (colander, ladle) and the rhythmic action are identical, the specific words in the audio ('FAITH' vs '67') and text overlays differ. A model might treat these as distinct audio/text segments rather than recognizing the underlying 'SYBAU X' chanting format and the specific sound effect as a shared meme template, which requires a deeper understanding of cultural trends and meme structures beyond simple keyword or audio matching."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7583298662386650389_7603817886603300103/analysis.json b/tmp/proactive_publish_20260313/7583298662386650389_7603817886603300103/analysis.json
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+{
+  "消费视频主题": "A man records himself speaking a religious reflection about trusting God's timing and control over life, with text overlays of his speech.",
+  "投稿视频主题": "A montage of nature scenes (mountains, valleys, flowers) accompanies the exact same religious reflection and text overlays as the consumption video.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "The publish video directly reuses the exact same audio (spoken reflection and background music) and identical text overlays from the consumption video, indicating a strong causal relationship where the consumption video provided the content for the publish video.",
+  "model_error_analysis": "The ML model likely failed because it focused primarily on visual features, detecting a significant difference between the selfie-style video of a man and the nature montage. It probably did not adequately weigh the identical audio (spoken content and background music) and text overlays, which are the strongest indicators of a causal relationship in this instance, as the core content is directly reused despite visual changes."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7583769463078800643_7603057302106656022/analysis.json b/tmp/proactive_publish_20260313/7583769463078800643_7603057302106656022/analysis.json
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+{
+  "消费视频主题": "A montage showcasing promotional materials and merchandise for various animated movies like Alvin and the Chipmunks, Rio 2, and The Lego Movie.",
+  "投稿视频主题": "A Mii character explains various facts and trivia about Link from The Legend of Zelda video game series, using game footage and character images.",
+  "主题相似": "抽象主题相似",
+  "相似元素": [],
+  "reasoning": "Both videos feature popular fictional characters from media franchises. Video 1 focuses on animated movie characters and their promotional materials, while Video 2 provides trivia about a specific video game character (Link). The connection is at a broad thematic level of popular culture and fictional IPs, but not specific enough to be causal or fine-grained.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because the visual content, audio, and specific IPs are entirely different. Video 1 shows real-world photos of movie displays, while Video 2 uses game footage and a Mii character with French narration. A model would struggle to connect 'animated movies' with 'video game characters' at an abstract level of 'fictional media IPs' without deeper semantic understanding beyond direct visual, audio, or keyword matches."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7584143881545977110_7593173975707028758/analysis.json b/tmp/proactive_publish_20260313/7584143881545977110_7593173975707028758/analysis.json
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@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A young German rapper reacts to and raps along with his first song, which he recorded at age 12, featuring street-style lyrics.",
+  "投稿视频主题": "A German rapper performs his street-style rap song in various urban settings for a music video.",
+  "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 specific genre of German street rap. The consumption video features a rapper reacting to his childhood rap song, while the publish video is a professionally produced rap music video. They share the same specific musical genre and the subject type (male rapper).",
+  "model_error_analysis": "The ML model likely failed to detect the relationship because it might not recognize the specific subgenre of 'German street rap' as a strong thematic link without explicit audio fingerprinting for the *same* song. The visual content is different (a reaction video vs. a music video with diverse outdoor/indoor shots), and the model may not have connected the concept of 'rapper reacting to his old rap' with 'rapper performing new rap' as strongly related within the same niche, especially if it relies heavily on direct audio matches or visual templates rather than a deeper understanding of genre and artist type."
+}
\ No newline at end of file
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+{
+  "消费视频主题": "视频展示了从泥泞小路到雪地冬景的自然风光，并配有文字“今日金句：耶稣爱你”和一首情感歌曲。",
+  "投稿视频主题": "视频展示了郁郁葱葱的热带棕榈树林，并配有圣经经文“以赛亚书 66:13 '即使在你最艰难的日子里，上帝也与你同在'”和一首缓慢的器乐歌曲。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "两个视频都采用了相同的创作模式：在自然风景视频上叠加宗教或励志文字，并配以缓慢、情感化的背景音乐。这是一种常见的社交媒体内容创作模板或'玩法'，旨在传递精神或鼓舞人心的信息。",
+  "model_error_analysis": "模型可能未能识别出这种因果关系，因为它可能过于关注具体的文本内容（'耶稣爱你'与'上帝与你同在'不同）、具体的音乐曲目（虽然风格相似但并非同一首歌）以及视觉上的差异（冬季景观与热带景观）。模型可能缺乏对这种特定'励志/宗教信息+自然风光+情感音乐'作为一种流行内容模板的深层语义理解和文化背景知识，从而无法将这些表面上不同的元素归结为相同的创作玩法。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7585337388545723681_7593386207040507169/analysis.json b/tmp/proactive_publish_20260313/7585337388545723681_7593386207040507169/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..344b6525f0347d633a5c15e32612b5ec6fa71b8d
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7585337388545723681_7593386207040507169/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "一群年轻男子在户外，穿着羽绒服，对着一棵装饰过的圣诞树跳着特定的舞蹈动作，视频中显示歌曲名为“The Big One Song”。",
+  "投稿视频主题": "一名年轻男子在阳台上，穿着类似的羽绒服并戴着面罩，对着相同的歌曲跳着与消费视频中完全一致的舞蹈动作，视频中也显示歌曲名为“The Big One Song”。",
+  "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": "两个视频使用了完全相同的背景音乐（“The Big One Song”），并展示了完全一致的特定舞蹈动作。视频中的文字也明确指出了相同的歌曲名称。此外，视频中的拍摄对象都是穿着类似羽绒服的年轻男子，这表明了高度的模仿性和因果关系。",
+  "model_error_analysis": "ML模型可能未能识别出视频中使用的特定歌曲（“The Big One Song”）及其作为流行趋势或挑战的性质。模型可能将不同的拍摄环境（户外与阳台，多人与单人）视为主要差异，而忽略了核心的、完全一致的舞蹈动作和背景音乐。此外，模型可能没有深入理解文本叠加的语义，未能将其作为连接两个视频的关键线索。对于这种依赖于特定音乐和舞蹈动作的病毒式挑战，模型需要更强的音频识别能力、细粒度的动作识别能力以及对社交媒体趋势的上下文理解。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7586774649753718038_7593408077811207427/analysis.json b/tmp/proactive_publish_20260313/7586774649753718038_7593408077811207427/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..62a61188f9d2d253762e6e4126733044bade3a2c
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7586774649753718038_7593408077811207427/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A person humorously attempts to work on a car's wheel without a jack, accompanied by a comedic audio.",
+  "投稿视频主题": "A purple Mercedes-Benz C63 AMG Coupe is showcased at an electric charging station with a specific audio track.",
+  "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 cars. Video 1 features a person working on a car's wheel, while Video 2 showcases a modified car. Despite the different specific activities, the overarching theme of 'cars' connects them at a fine-grained level.",
+  "model_error_analysis": "The ML model likely failed because it couldn't generalize the 'cars' theme across different sub-genres. Video 1 is a comedic skit about car maintenance, while Video 2 is an aesthetic car showcase. The model might have focused too much on the differing specific actions (person working vs. car being displayed) and distinct audio tracks (comedic voiceover vs. melodic electronic music), missing the common primary subject of 'cars' that links them at a fine-grained thematic level."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7588310732303879432_7595998237404761362/analysis.json b/tmp/proactive_publish_20260313/7588310732303879432_7595998237404761362/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..c0fa25fca138abe080d0c3e3b14ee91e077f1e91
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7588310732303879432_7595998237404761362/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A scenic video showcasing a pier decorated with a large Christmas tree-like structure and candy canes by the ocean, with people walking and swimming, set to a popular Spanish meme audio about saving money.",
+  "投稿视频主题": "A vlog-style video documenting a lively beach party event in Puerto Vallarta, featuring friends, dancing, beer, and a dog, with humorous narration and the same popular Spanish meme audio about saving money.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐"
+  ],
+  "reasoning": "Both videos utilize the exact same popular Spanish meme audio, which is used to add a humorous and ironic commentary on the depicted scenes (a beautiful but potentially expensive holiday destination in video 1, and a lively beach party/event in video 2). This shared meme audio indicates a direct causal relationship as it represents a 'same meme or viral format/玩法'.",
+  "model_error_analysis": "The ML model likely failed because it did not recognize the specific meme context and viral usage of the shared audio. While it might identify the audio, it may not understand its cultural significance as a meme used for ironic commentary. The visual content of the two videos is quite different (a scenic pier vs. a beach party with specific activities like dancing and a stage), which could lead a visually-focused model to classify them as unrelated. The model would need to understand the nuanced, ironic application of the audio, which requires cultural and semantic understanding beyond simple audio fingerprinting or broad visual similarity."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7589478401866616084_7592464439727623445/analysis.json b/tmp/proactive_publish_20260313/7589478401866616084_7592464439727623445/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..ec2808c535e3cc5e11ca2665d1bb851c4f3f1351
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7589478401866616084_7592464439727623445/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "视频展示了多件待售的矿物晶体和化石，包括球形珊瑚化石、菊石化石、拉长石板、蓝色文石球、绿色萤石球和玛瑙晶洞，并配有文字预告直播销售。",
+  "投稿视频主题": "视频展示了一块高品质的木化石板，通过手持旋转展示其不同侧面和纹理，并配有文字预告直播销售。",
+  "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": "两个视频都属于高度相似的水晶/矿物销售利基市场，采用相同的展示方式（手持并旋转展示物品），并使用相似的文案格式来预告“直播销售”。背景音乐风格也高度一致，共同构成了一个可识别的内容模板，表明消费视频很可能启发了投稿视频的创作。",
+  "model_error_analysis": "ML模型可能未能识别这种相似性，因为它可能侧重于视频中展示的具体物品（不同类型的晶体/矿物），而不是整体的展示格式、文案结构和音乐风格。这种“直播预告+手持展示矿物”的组合是一种特定社群内的内容模板，模型可能缺乏识别这种利基模板或其因果关系的文化/领域知识，尤其是在音乐并非完全相同的情况下。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7589598278531009813_7604139924731809045/analysis.json b/tmp/proactive_publish_20260313/7589598278531009813_7604139924731809045/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d370e7659075c05bc2a4f4619f3e48044ad7b4c1
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7589598278531009813_7604139924731809045/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "视频展示了AI生成的可爱宝宝穿着动物服装骑着兔子、大象、猫和熊猫等动物的场景。",
+  "投稿视频主题": "视频展示了AI生成的可爱男孩在房间里与一只小猫玩耍的场景。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "拍摄对象"
+  ],
+  "reasoning": "两个视频都采用了高度相似的AI生成卡通画风，角色设计（Q版宝宝和可爱动物）以及整体的明亮、愉快的氛围。这种独特的AI艺术风格和角色类型构成了一种流行的创作模板或玩法，表明两者之间存在因果关联。",
+  "model_error_analysis": "ML模型可能未能识别出这种特定且高度相似的AI生成艺术风格和Q版角色设计作为一种'病毒式格式/玩法'。模型可能更侧重于识别视频中的具体动作（骑行 vs 玩耍）或不同动物种类，而忽略了将这些视频归类为同一AI创作趋势或模板的关键视觉特征，从而导致误判为不相关。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7590080459309124886_7602942433009159446/analysis.json b/tmp/proactive_publish_20260313/7590080459309124886_7602942433009159446/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c9dc04c6d47b91af5f79613fc2f60468bea2fa1
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7590080459309124886_7602942433009159446/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "一个小女孩在迪士尼乐园里，用“我的膝盖疼”（My knee hurts）和“哪个膝盖？”（Which knee?）的对话引出“迪士尼”（Dis Knee）的谐音梗，并伴随特定音乐。",
+  "投稿视频主题": "一个年轻女子和男子在主题公园里，重复了“我的膝盖疼”（My Knee Hurts）和“哪个膝盖？？”（Which Knee??）的对话，引出“迪士尼！！！”（DIS-NEYYY!!!）的谐音梗，并使用相同的音乐。",
+  "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": "两个视频使用了完全相同的音频（包括对话和背景音乐），文案内容和表达方式高度一致，并且都围绕“迪士尼”的谐音梗展开，在主题公园背景下做出了相同的抬腿动作。这表明投稿视频是直接模仿消费视频的病毒式玩法和格式。",
+  "model_error_analysis": "ML模型可能未能识别出视频中包含特定对话和音乐的完整音频片段作为强烈的因果信号。模型可能也难以理解“Dis Knee”和“DIS-NEYYY!!!”之间的谐音梗和语义关联，这需要更深层次的语言和文化理解。此外，尽管两个视频都发生在主题公园，但具体的视觉背景可能有所不同，导致模型无法仅凭视觉判断出两者都与“迪士尼”这一IP相关联，从而错过了这一特定梗的因果关系。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7590122947935735062_7602760876478745878/analysis.json b/tmp/proactive_publish_20260313/7590122947935735062_7602760876478745878/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..37fb20f9d68e01952cbcfc42ce8936ed2cbc5e20
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7590122947935735062_7602760876478745878/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A young woman with long red hair is lipsyncing to a foreign song, smiling and making hand gestures.",
+  "投稿视频主题": "A different young woman is lipsyncing to the exact same foreign song in a dark room with a sparkling stars filter.",
+  "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 different individuals lipsyncing to the identical foreign language song, which is a strong indicator of a direct causal relationship.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it may not have robust audio fingerprinting capabilities to identify the exact same song being used across two visually distinct videos. The visual elements (different subjects, clothing, lighting, and the presence of a unique 'sparkling stars' filter in the publish video) are quite different, which could mislead a visually-focused model. The core similarity lies in the shared audio track and the specific action of lipsyncing to it, which requires strong audio-visual correlation or dedicated audio matching."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7590736059038698760_7604236963700329736/analysis.json b/tmp/proactive_publish_20260313/7590736059038698760_7604236963700329736/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..730163964bd51707b2754f928ea65f42ad18ba9c
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7590736059038698760_7604236963700329736/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A young man stands on a bridge over a river, hesitates, and then jumps into the water.",
+  "投稿视频主题": "The same young man comically attempts a golf swing in a grassy outdoor area.",
+  "主题相似": "都是自拍/他拍/随拍",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature the same individual engaging in casual outdoor activities, presented in a personal, informal style. The primary similarity is the recurring subject.",
+  "model_error_analysis": "The ML model likely failed to detect the relationship because it focused on the distinct activities (jumping into water vs. comedic golf swing) and different visual settings (river/bridge vs. grassy field) and audio tracks. It probably lacked a robust person re-identification component or the ability to group videos by the same individual creator/subject when the specific content and context vary significantly, leading it to classify them as unrelated based on activity and scene features."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7591396054570896660_7602174366645865736/analysis.json b/tmp/proactive_publish_20260313/7591396054570896660_7602174366645865736/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e8e497dacfce86ec09c2df2849f270417aef4d1
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7591396054570896660_7602174366645865736/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A woman rescues an abandoned, injured dog from a supermarket parking lot, takes it to the vet for treatment, and seeks an adoptive family for it.",
+  "投稿视频主题": "A compilation of short clips showcasing a fluffy white pet dog, highlighting its cuteness and affectionate behavior.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos center around pet dogs and evoke positive, heartwarming emotions related to animal companionship. The consumption video, a rescue story, could inspire a user to share their own beloved pet, leading to the publish video.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to focusing on superficial differences rather than the underlying thematic and emotional connection. The dogs are different breeds, the settings vary significantly (supermarket/vet vs. home), and the specific narratives are distinct. A model relying on exact audio matches or specific visual features of the dog/environment would miss the shared 'pet dog' theme and the similar emotional tone conveyed by the background music, which is a strong indicator of inspiration for human annotators."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7591603142207474952_7592657430761295124/analysis.json b/tmp/proactive_publish_20260313/7591603142207474952_7592657430761295124/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..638c774a63061f297aa77ebfd1d3187459fd78c4
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7591603142207474952_7592657430761295124/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A white dog attempts to squeeze its body through the bars of a metal fence.",
+  "投稿视频主题": "A cat and a raccoon are captured by a night vision camera, standing on their hind legs and playfully fighting near a trash can.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature animals in engaging or humorous situations. The consumption video shows a dog comically struggling with a fence, and the publish video shows a cat and a raccoon interacting. While the specific animals and their actions differ, both fall under the fine-grained thematic category of 'animal behavior' or 'pets/wildlife interactions'.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because the specific actions, visual settings (daylight street vs. night vision backyard), and audio tracks are completely different. The model might not have generalized effectively from 'dog struggling' to 'cat and raccoon fighting' within the broader 'animal content' vertical, focusing too much on low-level visual and audio features rather than the fine-grained thematic connection of animal behavior."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7591633885876833543_7592914268626930952/analysis.json b/tmp/proactive_publish_20260313/7591633885876833543_7592914268626930952/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..af3d293f4dc982a918f846ea612981d3467aee81
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7591633885876833543_7592914268626930952/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A tattooed woman with sunglasses is lipsyncing to an Indonesian song outdoors in front of cars, performing various hand gestures and facial expressions.",
+  "投稿视频主题": "A woman is lipsyncing to the same Indonesian song indoors against a blue wall, mimicking the gestures and facial expressions from the consumption video.",
+  "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 different women lipsyncing to the exact same song, performing highly similar hand gestures and facial expressions in sync with the lyrics. This indicates a direct causal relationship where the publish video was inspired by the consumption video's use of the specific audio and its associated performance.",
+  "model_error_analysis": "The ML model likely failed because it did not prioritize the identical audio track as the primary causal feature. It might have been overly influenced by the significant visual differences between the two videos, such as different subjects, backgrounds, and clothing. While the '主体行为/形态' (subject actions/gestures) are similar, the most direct and undeniable causal link is the shared audio, which a robust model should detect regardless of visual discrepancies."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592127916369022215_7592811493075225877/analysis.json b/tmp/proactive_publish_20260313/7592127916369022215_7592811493075225877/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..774114a229052e8dc6519689938cb1e853046245
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592127916369022215_7592811493075225877/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "一位孕妇在车内讨论与伴侣为即将出生的女儿选择名字的困难，并分享自己不喜欢本名而使用昵称的经历，向观众征集婴儿名字建议。",
+  "投稿视频主题": "一对夫妇通过ChatGPT生成了一系列照片，展示了他们从两人世界到拥有三个孩子的家庭成长过程，所有照片中他们都穿着迷彩服在户外。",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "消费视频中孕妇讨论的是为孩子取名，围绕着家庭和孩子的诞生；投稿视频则通过AI生成图片展示了家庭成员（孩子）的增加。两者都围绕着“家庭”和“孩子”这一细粒度主题展开，消费视频可能启发了用户对未来家庭的思考和创作。",
+  "model_error_analysis": "ML模型可能未能识别出两个视频之间关于“家庭”和“孩子”的细粒度主题联系。模型可能过于关注表层特征，例如视频形式（一个是对口型/讲话，另一个是图片蒙太奇）、具体内容（一个是取名，一个是AI生成家庭照片）和音频（一个是人声，一个是背景音乐），而忽略了两者在“家庭组建与孩子”这一核心概念上的深层关联。模型可能缺乏对这种抽象主题关联的理解能力，特别是当内容表现形式差异较大时。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592292714314566934_7603000520394968342/analysis.json b/tmp/proactive_publish_20260313/7592292714314566934_7603000520394968342/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..6703d95c769f618c4bfa3c0d2b2b0abed2748bc9
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592292714314566934_7603000520394968342/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "A white BMW car is showcased from various angles with slow-motion effects and transitions, set to a specific song.",
+  "投稿视频主题": "A white Volkswagen Golf car is shown, first dirty, then undergoing a cleaning and detailing process, and finally clean, using similar slow-motion effects, transitions, and the exact same background song.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature white cars and utilize the exact same background music. They also share a highly similar visual presentation style, including slow-motion shots, dynamic camera angles, and transitions, to showcase the car's aesthetics and details. Video 2 extends this by adding a car cleaning/detailing process, but the overall format and audio strongly suggest inspiration from Video 1's aesthetic presentation.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it missed the strong signal of the exact same background music being used for a similar content type (car showcase/detailing). While it might identify 'cars' as a common theme, it probably didn't recognize the specific audio as a trending sound associated with this particular visual format or '玩法' within the car community. The model might also struggle to connect the subtle but consistent visual style elements (slow-motion, specific transitions, multi-angle presentation) across different car models as a shared creative template."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592379393456999688_7592812522206514452/analysis.json b/tmp/proactive_publish_20260313/7592379393456999688_7592812522206514452/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..298ea21abcf33f2529336c55c48a4090b3f7565f
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592379393456999688_7592812522206514452/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A red Tesla Model Y receives a full front paint protection film installation, showcasing the detailed process of washing, inspection, and film application.",
+  "投稿视频主题": "A Porsche Cayenne's interior gloss black trim pieces are protected with satin paint protection film to prevent swirls and fingerprints, demonstrating the application process.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos are centered around the highly specific niche activity of applying Paint Protection Film (PPF) to car surfaces. While one focuses on the exterior of a Tesla and the other on the interior of a Porsche, the core product, installation techniques (squeegeeing, trimming), and purpose (surface protection) are identical. The text overlays also use similar specialized terminology related to PPF.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might have focused on superficial differences such as the car brand (Tesla vs. Porsche), the specific car part (exterior vs. interior), or the color. It likely missed the strong semantic and visual cues of the highly specific 'PPF installation' activity, which involves distinct tools and techniques (squeegeeing, film manipulation) and shared terminology in the text overlays, indicating a direct thematic connection despite surface-level variations."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592395525857627448_7592424707811446034/analysis.json b/tmp/proactive_publish_20260313/7592395525857627448_7592424707811446034/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d55c05bf89ae4c8483d157046dc9d1d362f119fd
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592395525857627448_7592424707811446034/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A promotional video for a psychological horror book titled 'Don't Wake Up', featuring dark, eerie imagery and text describing the book's plot.",
+  "投稿视频主题": "A man reviewing several horror movie Blu-rays he acquired from a bargain bin, including 'The Evil Dead' series, 'Dog Soldiers', and 'Silent Hill'.",
+  "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 horror genre and horror media. The consumption video promotes a horror book, while the publish video reviews horror movies. A Chucky doll/box, a specific horror IP, is visible in the background of both videos, indicating a shared interest in the horror universe.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to the difference in content format (book promotion with cinematic clips vs. talking-head movie review) and audio. It probably missed the fine-grained thematic connection of the horror genre across different media types and the subtle visual cue of the shared 'Chucky' IP in the background, which requires a deeper understanding of cultural references and niche interests beyond surface-level features."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592396786472455445_7592776503407037716/analysis.json b/tmp/proactive_publish_20260313/7592396786472455445_7592776503407037716/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..669145088d701881e51c84b4301e53cfcce1a7b6
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592396786472455445_7592776503407037716/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A young man showcases various motorcycles for sale at a dealership, listing prices and features, with a text overlay advertising monthly offers.",
+  "投稿视频主题": "Two different customers give positive testimonials after purchasing motorcycles, including models seen in the consumption video, from what appears to be a dealership.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "拍摄对象",
+    "语句文案"
+  ],
+  "reasoning": "The consumption video is a promotional advertisement for a motorcycle dealership, showcasing bikes for sale. The publish video features satisfied customers giving testimonials after purchasing motorcycles, including models present in the consumption video's inventory, strongly implying a direct causal link where the dealership's promotions led to these sales.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship due to the nuanced commercial context. While both videos feature motorcycles, the model might have missed the direct link between a dealership's sales pitch (consumption video) and customer testimonials for purchases (publish video). It may have struggled to infer the shared business entity or the complementary roles of seller and buyer, especially without identical audio or visual templates. The model might have focused on superficial differences in presentation (seller showcasing vs. customer interview) rather than the underlying thematic connection of a specific business's sales cycle."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592406759860423943_7592469167501102344/analysis.json b/tmp/proactive_publish_20260313/7592406759860423943_7592469167501102344/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a63113683798ba85bea4004a6c79623b956f13b4
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592406759860423943_7592469167501102344/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "A man shares a healthy, high-protein, low-calorie drink option from Tim Hortons as part of a 15-day healthy cheat meal challenge.",
+  "投稿视频主题": "A shirtless man poses and flexes his muscles in a gym, showcasing his physique.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [],
+  "reasoning": "Both videos fall under the specific interest vertical of fitness and healthy living. The consumption video offers a diet tip for a healthy lifestyle, while the publish video displays a physique, which is a direct outcome of fitness and diet efforts.",
+  "model_error_analysis": "The ML model likely failed because there are no direct shared elements such as identical audio, visual templates, or specific actions. The connection is thematic, linking diet/nutrition (consumption video) with bodybuilding/physique (publish video) within the broader 'fitness' category, which requires a deeper semantic understanding of related concepts rather than surface-level feature matching."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592439822283705607_7592708834959904001/analysis.json b/tmp/proactive_publish_20260313/7592439822283705607_7592708834959904001/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..283fda97418bc23aa9bfa3c0edc8603d838af881
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592439822283705607_7592708834959904001/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "A grey Chevrolet car is showcased in a car dealership, with a voiceover describing its features and a phone number for inquiries.",
+  "投稿视频主题": "A man in a car dealership speaks directly to the camera, listing cars that have been sold and cars still available, with a phone number overlay.",
+  "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 from the same car dealership, featuring the same person promoting used cars. The background music is identical, the spoken content is by the same individual, and the phone number overlay is the same. The grey Chevrolet car from video 1 is also visible in video 2, confirming they are related to the same business and inventory.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might not have recognized the specific car dealership or the individual promoting the cars as the same entity across both videos. While the visual content differs (one focuses on a single car, the other on the seller and general inventory), the identical background music, the same person's voice and presence, and the consistent phone number overlay are strong signals of a direct connection that a model might miss if it primarily relies on visual object detection or broad thematic categories without deeper cross-modal (audio, text, visual identity) linking."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592441861743136007_7592686503755582727/analysis.json b/tmp/proactive_publish_20260313/7592441861743136007_7592686503755582727/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..1f3478a12f693bbdec819da169e1cf4352c1d5bd
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592441861743136007_7592686503755582727/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A young man practices his golf swing at a driving range, with a ChatGPT overlay discussing golfers' regrets about not starting younger.",
+  "投稿视频主题": "An older man demonstrates a golf putting technique indoors, explaining his grip and the importance of practice, concluding with a golf swing outdoors and a philosophical quote about golf.",
+  "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 are centered around the sport of golf. The consumption video shows a person practicing golf swings, and the publish video features a person demonstrating golf putting techniques and discussing golf philosophy. The core subject and activity (golf) are the same, despite differences in specific actions (driving vs. putting) and setting.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to the significant visual and contextual differences between the videos. Video 1 is an outdoor driving range scene with a young person and a specific text overlay format, while Video 2 is an indoor instructional video with an older person, different text overlays, and spoken commentary. The model might have focused on these superficial differences (age, setting, specific golf action, video style) rather than recognizing the overarching theme of 'golf' and the shared subject/activity of 'golfers playing golf'."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592612029127494934_7593372133087022358/analysis.json b/tmp/proactive_publish_20260313/7592612029127494934_7593372133087022358/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..328f85a671e9b5756964a4e675829398d6a85d98
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592612029127494934_7593372133087022358/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A young woman smiles and makes hand gestures in front of a mirror, reacting to the text overlay about treating university like a side hobby.",
+  "投稿视频主题": "A montage of university life scenes, including the campus exterior, students in a cafe, a lecture hall, and studying on a laptop, all illustrating the meme about treating university as a side hobby.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案"
+  ],
+  "reasoning": "Both videos use the exact same viral text overlay/meme format about treating university as a side hobby. Video 1 is a personal reaction to the meme, while Video 2 is a montage illustrating the concept within a university setting. The shared specific meme indicates a strong causal relationship.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because the primary shared element is a specific textual meme, which requires robust text understanding and meme recognition. The videos have different background music and distinct visual content (a selfie reaction vs. a university montage), which would likely lead a model relying heavily on audio and visual features to classify them as dissimilar. The slight variation in the text overlay ('me' vs 'us') might also hinder exact string matching by the model."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592621669458480417_7593325946653003030/analysis.json b/tmp/proactive_publish_20260313/7592621669458480417_7593325946653003030/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..befed372a0e76a849e9199190c519fe092a4a3af
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592621669458480417_7593325946653003030/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "一位年轻女子在下雪的户外对一首德语歌曲进行口型对唱，并做出各种手势和面部表情。",
+  "投稿视频主题": "一位年轻女子在室内对同一首德语歌曲进行口型对唱，并做出类似的手势和面部表情。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "两段视频都使用了完全相同的德语背景音乐进行口型对唱，并且表演者都做出了相似的表情和手势。这种共享的特定歌曲和表演形式是因果关系的最强证据。",
+  "model_error_analysis": "ML模型可能未能识别出这种因果关系，因为它可能没有准确地识别出两段视频使用了完全相同的特定音频。尽管两者都是口型对唱，但视频中的人物、服装和环境都完全不同，如果模型主要依赖视觉特征或对音频指纹识别不够精确，就可能将它们判断为不相关。模型可能将'lipsync'视为一个宽泛的类别，而没有识别出'same song lipsync'这一更具体的因果关系。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592630277092936980_7592934574200605974/analysis.json b/tmp/proactive_publish_20260313/7592630277092936980_7592934574200605974/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d21b479bd24e18d2e9b5f1a4680847765edc48e3
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592630277092936980_7592934574200605974/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A woman in a green hoodie performs a trending dance routine to a specific song in a white-walled room.",
+  "投稿视频主题": "A woman in a white crop top and ripped jeans performs the exact same trending dance routine to the same specific song, in black and white, with the text 'My fyp lately 😉'.",
+  "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 different individuals performing the identical trending dance routine to the exact same background music. This indicates a direct causal relationship, as the publish video is clearly replicating a viral dance challenge or trend seen in the consumption video.",
+  "model_error_analysis": "The ML model likely failed because it focused too much on superficial visual differences such as the different individuals, clothing, backgrounds, and the black and white filter in the publish video versus the color in the consumption video. It missed the strong causal signals of the identical specific dance choreography performed to the exact same trending audio, which is a key indicator of a viral challenge or meme."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592662940269006113_7593135968987696406/analysis.json b/tmp/proactive_publish_20260313/7592662940269006113_7593135968987696406/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..087e856b0f44f87127501613e9e24500d1a3f354
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592662940269006113_7593135968987696406/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A small striped kitten stands on its hind legs and moves its front paws to an upbeat song.",
+  "投稿视频主题": "A fluffy orange kitten is shown being bathed in a tub, sitting on a sink, wrapped in a towel, and finally resting on a couch.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature cute kittens as the main subject, falling under the fine-grained theme of pet cats. However, the specific activities (dancing vs. bathing) and background music are different, indicating a thematic correlation rather than direct causation from a specific meme or challenge.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because it might prioritize shared audio or specific creative actions/challenges for causal links. While both videos feature kittens, their specific activities and background music are distinct. The model might not have weighed the 'subject of shooting' (kittens) strongly enough to establish a 'related' connection without other overlapping elements like a common meme or audio."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592695844491644178_7593247873295289622/analysis.json b/tmp/proactive_publish_20260313/7592695844491644178_7593247873295289622/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..422dd21209242dfbfec1f99677a0e41894d18ea4
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592695844491644178_7593247873295289622/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A young woman with braids and a yellow flower in her hair lipsyncs to a male voice audio with a foreign language text overlay.",
+  "投稿视频主题": "A young woman uses a dog face filter while lipsyncing to the same male voice audio with a foreign language text overlay, filmed vertically while lying down.",
+  "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 feature different young women lipsyncing to the exact same spoken audio. They also share highly similar text overlays, indicating they are participating in the same viral trend or challenge associated with this specific audio and message.",
+  "model_error_analysis": "The model likely failed to detect the causal relationship due to several factors: 1) It might not have accurately matched the spoken audio, especially if it's dialogue rather than a distinct song, or if there are minor variations in recording. 2) The text overlays are in a foreign language (Uzbek), which could pose a challenge for cross-lingual text matching. 3) The visual differences (different individuals, one using a dog filter, different camera angles/settings) might have led a visually-biased model to classify them as unrelated, overlooking the strong audio and text commonalities that define the meme/trend."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7592983455659543830_7593423283710610710/analysis.json b/tmp/proactive_publish_20260313/7592983455659543830_7593423283710610710/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..7023f40aca03b412fbccf810c468d083878cc349
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7592983455659543830_7593423283710610710/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "一个年轻男子在客厅里对着电视背景下的阿拉伯歌曲进行唇语对口型表演，并做出手势。",
+  "投稿视频主题": "一个年轻男子在装饰灯光下的房间里对着同一首阿拉伯歌曲进行唇语对口型表演，并模仿手势。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "两个视频都使用了完全相同的阿拉伯歌曲进行唇语对口型表演，并且投稿视频中的男子模仿了消费视频中男子的一些特定手势和表情，这表明了直接的因果关系。",
+  "model_error_analysis": "ML模型可能未能识别出这两个视频使用了完全相同的背景音乐，这通常需要精确的音频指纹识别技术。此外，尽管表演者和背景不同，但投稿视频中对消费视频特定手势和表情的模仿（主体行为/形态）可能过于细微，模型难以通过视觉特征进行准确匹配，从而导致误判为不相关。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7593033792315575574_7593099150867172630/analysis.json b/tmp/proactive_publish_20260313/7593033792315575574_7593099150867172630/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..e0e73b916588562e09a88249fcad09a55d2cc3f6
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7593033792315575574_7593099150867172630/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "视频展示了一位DJ在Pioneer DJ设备上播放并预告即将发布的新电子音乐曲目，屏幕上显示着音轨波形和曲目信息。",
+  "投稿视频主题": "视频以一个旋转的圆形画框展示了一幅俯瞰视角下，一个人站在悬崖边眺望大海的画面，作为一首电子音乐曲目的视觉化宣传，并提示已在Soundcloud发布。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐"
+  ],
+  "reasoning": "两个视频使用了完全相同的背景音乐。消费视频是DJ在推广这首即将发布的音乐，而投稿视频则是这首音乐发布后的视觉化宣传。音乐是两者之间最直接的因果联系。",
+  "model_error_analysis": "ML模型可能主要依赖视觉内容或文本匹配来判断相似性。然而，这两个视频的视觉内容（DJ设备与海边风景）和直接文本（发布时间/平台）差异很大。模型可能未能识别出两个视频中完全相同的背景音乐，或者没有将音乐作为判断因果关系的最重要特征。要正确识别这种关系，模型需要强大的音频指纹识别能力，并能理解不同形式的音乐推广内容（DJ现场播放与专辑视觉化）之间的关联。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7593219919349566741_7595664852438338823/analysis.json b/tmp/proactive_publish_20260313/7593219919349566741_7595664852438338823/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..844234aa148e4ecbb88447547c3af0886badf878
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7593219919349566741_7595664852438338823/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A young woman lipsyncs to a Spanish song, with text overlay asking about 'kisses that taste like iron' and making a kissing face.",
+  "投稿视频主题": "A young man lipsyncs to the exact same Spanish song, with text overlay about 'big kisses that taste like iron' and making a kissing face.",
+  "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 and a highly similar text overlay/meme format ('kisses that taste like iron'), indicating a direct causal relationship where the publish video was inspired by the consumption video's format and audio.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it missed the strong signals from the identical background music and the semantically identical, meme-driven text overlay. While the subjects are different, the combination of the specific audio and the specific phrase/meme format is a clear indicator of a viral trend. The model might have focused too much on visual differences or lacked robust cross-modal understanding to connect the audio and text as a single meme unit."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7593374120054656276_7604306674219863303/analysis.json b/tmp/proactive_publish_20260313/7593374120054656276_7604306674219863303/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..c43903429881702f1f6f4fdc437e60c146aa3877
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7593374120054656276_7604306674219863303/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "一群蒙面男子在夜晚的城市巷道中，随着说唱音乐摆姿势、做手势，并展示印有文字的T恤。",
+  "投稿视频主题": "一名蒙面男子在城市环境中，随着相同的说唱音乐摆姿势，视频中带有故障效果和歌词文本叠加。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "两段视频使用了完全相同的说唱音乐，并且都展现了蒙面男子在城市背景下，以该音乐类型特有的姿态和手势进行拍摄，具有强烈的因果关联。",
+  "model_error_analysis": "ML模型可能未能识别出两段视频使用了完全相同的背景音乐，这是最强的因果信号。模型可能过于依赖视觉特征，而忽略了音频匹配的重要性。此外，模型可能未能将蒙面人物、城市背景以及特定的姿势和手势识别为该音乐流派（drill music）的特定视觉风格和行为模式，从而错失了主题和行为上的深层相似性。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7593727005841968391_7595431144884129035/analysis.json b/tmp/proactive_publish_20260313/7593727005841968391_7595431144884129035/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..536b5d038a1be55772a8d0a75b707d56a4f9dc39
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7593727005841968391_7595431144884129035/analysis.json
@@ -0,0 +1,13 @@
+{
+  "消费视频主题": "一个关于在Roblox游戏中玩家表现出色被指责使用外挂的梗图视频，通过一系列动画角色和文字描述了人们的反应。",
+  "投稿视频主题": "一个关于在游戏中玩家表现出色被指责使用外挂的梗图视频，通过一系列动画角色和文字描述了人们的反应，与消费视频使用了相同的梗格式和音频。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "语句文案",
+    "主体行为/形态"
+  ],
+  "reasoning": "两个视频都使用了完全相同的网络梗格式和背景音频，通过替换不同的游戏动作和角色，表达了玩家因表现过于出色而被指责使用外挂的幽默情景。这种高度一致的模版复用和特定音频的使用，表明投稿视频直接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梗图的因果关系，原因可能包括：1. 视觉元素：尽管是相同的梗格式，但视频中使用的具体角色图片（如Roblox角色、鸡肉角色、不同的动画表情包）是不同的，模型可能侧重于具体的视觉内容而非抽象的模版结构。2. 文本内容：虽然文本结构和含义高度相似，但具体的关键词（如'parrys' vs 'espadazos'）有所不同，模型可能无法理解这种'填空式'的文本模版复用。3. 音频：虽然音频完全相同，但如果模型对短时或特定梗音的识别能力不足，或者其特征提取侧重于音乐而非模因音频指纹，则可能无法将其作为强关联信号。4. 缺乏对网络文化梗的语义理解：模型可能难以理解这种跨视频的抽象模因格式复用，这需要更深层次的文化和语境理解。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7593819989833026834_7604240520432520466/analysis.json b/tmp/proactive_publish_20260313/7593819989833026834_7604240520432520466/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..f8faca927cac5423afbe8be21ade3bdea133af4a
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7593819989833026834_7604240520432520466/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "A woman in a car discusses the benefits of moving to Vancouver from Toronto, highlighting the active lifestyle options like hiking and skiing, and mentioning going to the gym.",
+  "投稿视频主题": "A woman films herself in a gym, showing her workout attire and starting a treadmill session, with the text 'movement' overlaid.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [],
+  "reasoning": "The consumption video discusses and promotes an active lifestyle, explicitly mentioning going to the gym, hiking, and skiing. The publish video directly shows a gym workout, aligning with the 'fitness' or 'active lifestyle' vertical mentioned in the consumption video.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to the lack of direct visual or audio overlap. Video 1 is a talking-head video in a car, while Video 2 is a gym workout montage with music. The thematic connection relies on understanding the spoken content in Video 1 (mentioning 'going to the gym,' 'hiking,' 'skiing') and relating it to the visual content of Video 2 (a gym workout). A model might struggle to bridge this gap without robust ASR and semantic understanding capabilities to connect spoken activities to visually depicted activities."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7594557794372652309_7604204623724809479/analysis.json b/tmp/proactive_publish_20260313/7594557794372652309_7604204623724809479/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..42ec3466c7a0cc5d915af8ad6ad3f3fb22b22c40
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7594557794372652309_7604204623724809479/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "A video featuring a spoken Christian prayer for strength and victory through the Holy Spirit, with glowing text overlays appearing over a driving shot on a road.",
+  "投稿视频主题": "A video presenting reflective Christian prayers and quotes from Saint Augustine of Hippo, with text boxes appearing over various symbolic and nature-themed backgrounds.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [],
+  "reasoning": "Both videos share a fine-grained thematic similarity as they are deeply rooted in Christian spirituality, focusing on prayer, faith, and divine intervention. While the specific prayers and visual styles differ, the core subject matter of spiritual devotion and seeking God's power is consistent.",
+  "model_error_analysis": "The ML model likely failed due to significant differences in low-level visual and audio features. The background visuals (driving vs. praying hands/nature/candle) are entirely distinct. The specific background music tracks are different, and the spoken content, while both religious, uses different voices and exact phrases. The text overlay styles (glowing, word-by-word vs. static text boxes) also vary. A model relying on these surface-level features would struggle to identify the underlying niche semantic similarity of Christian prayer and spiritual declarations, which requires a deeper contextual understanding of religious themes rather than direct visual or auditory matches."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7594990951328746808_7595755849885289748/analysis.json b/tmp/proactive_publish_20260313/7594990951328746808_7595755849885289748/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d8fc5cf5dfa60ce6dc39e4170901c8679c09b50f
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7594990951328746808_7595755849885289748/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A horse racing track or rodeo arena is completely flooded with muddy water, with several horses standing in the submerged area.",
+  "投稿视频主题": "Two horses with jockeys are shown racing on a dirt track, with text overlays about winning a race.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are related to horse racing. The consumption video shows a flooded horse racing venue, while the publish video shows an actual horse race. The common element is the specific subject of horse racing, indicating a fine-grained thematic similarity.",
+  "model_error_analysis": "The ML model likely failed due to the significant visual differences between the two videos. Video 1 depicts a static, flooded scene, which might be classified as 'disaster' or 'weather event', while Video 2 shows a dynamic horse race, classified as 'sports' or 'equestrian'. The model might not have recognized the underlying 'horse racing' context as a shared fine-grained theme because the immediate visual cues (flooding vs. racing) are so distinct. It would require a deeper semantic understanding to connect the purpose of the flooded venue in video 1 to the activity in video 2."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595380926247341332_7602338775099837714/analysis.json b/tmp/proactive_publish_20260313/7595380926247341332_7602338775099837714/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..6b6837a6de0264915e2168d8786e4be108177dd5
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595380926247341332_7602338775099837714/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A fake WhatsApp chat features a K-pop idol's profile picture and a flirty voice message, with text saying 'Ni-ki, go to sleep'.",
+  "投稿视频主题": "A split-screen meme compares the creator's and their sister's preferences for members of the K-pop group ENHYPEN, with various clips of the idols.",
+  "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 specific K-pop group ENHYPEN. Video 1 features Ni-ki from ENHYPEN in a fake chat, and Video 2 is a meme comparing preferences for ENHYPEN members, indicating a shared, specific interest in the same celebrity IP.",
+  "model_error_analysis": "The ML model likely failed due to the significant difference in video formats (static chat screenshot with audio vs. dynamic split-screen video compilation). It might also struggle to recognize the same K-pop IP (ENHYPEN) when presented in different contexts and visual styles, especially if it relies on visual features of the entire frame rather than specific celebrity recognition. The model might also not effectively link the name 'Ni-ki' in the text/audio of video 1 to the visual recognition of ENHYPEN members in video 2, or generalize 'K-pop music' as a strong similarity signal if it's looking for exact audio matches."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595395129591024904_7595962701738741000/analysis.json b/tmp/proactive_publish_20260313/7595395129591024904_7595962701738741000/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..fa5ea149d43050826258a29f4ef2dfc136c3548d
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595395129591024904_7595962701738741000/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A wide shot of a large, energetic K-pop concert by BTS, featuring bright stage lights, pyrotechnics, and a crowd holding light sticks.",
+  "投稿视频主题": "A scenic landscape video filmed from a moving vehicle, showing a road, green fields, and mountains under a cloudy sky, with text imagining BTS visiting Ecuador.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature the same specific K-pop song by BTS ('IDOL') and are explicitly centered around the K-pop group BTS, with the publish video being fan content inspired by the artist shown in the consumption video.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because the visual content of the two videos is entirely different (a concert vs. a landscape). The model probably did not adequately weigh the significance of the identical background music (a specific BTS song) and the explicit textual reference to BTS in the publish video, which strongly links it to the BTS concert in the consumption video. It missed the strong IP and fandom connection driven by the audio and text, focusing too much on visual dissimilarity."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595407496525663506_7595842450577575179/analysis.json b/tmp/proactive_publish_20260313/7595407496525663506_7595842450577575179/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..46b0363a998d514a652fef871faf774c6dbe5329
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595407496525663506_7595842450577575179/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "The video explains the theological ideas of Noetus of Smyrna, a 2nd-century Christian presbyter, focusing on his monotheistic views and his understanding of God's unity and manifestation in Jesus Christ, which led to accusations of Patripassianism.",
+  "投稿视频主题": "This video presents a text-based explanation of how 'apostolic language' resolves 1700 years of theological divisions regarding the nature of God (Father, Son, Holy Spirit) by outlining 'revelational planes' to avoid misinterpretations by Trinitarian and Unitarian approaches.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [],
+  "reasoning": "Both videos delve into complex and niche Christian theological discussions about the nature of God (Father, Son, Holy Spirit) and historical doctrinal disputes. Video 1 discusses Noetus of Smyrna's monotheistic views and the Patripassianism controversy, which is a specific historical debate directly related to the broader Trinitarian/Unitarian issues that Video 2 attempts to resolve through its 'apostolic language' framework. The shared focus on specific theological concepts and historical debates within Christianity indicates a fine-grained thematic similarity.",
+  "model_error_analysis": "The ML model likely failed due to the highly semantic and nuanced nature of the similarity, which lacks direct superficial cues. There are no shared visual templates, identical audio, or direct text overlaps (different languages for text overlays). The connection between a historical theological controversy (Patripassianism in Video 1) and a proposed framework to resolve such controversies (Video 2) requires deep contextual understanding of Christian theology, which a model primarily relying on surface-level features or generic keyword matching might miss. The niche nature of the theological topic also makes it challenging for a general model to identify the causal link without specific domain knowledge."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595414619993246983_7595648604866350354/analysis.json b/tmp/proactive_publish_20260313/7595414619993246983_7595648604866350354/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c775ef98595cdfb9bf2e6e84d79c7cb6d98f93a
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595414619993246983_7595648604866350354/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A man performs heavy barbell squats in a gym with a spotter.",
+  "投稿视频主题": "A shirtless man poses in a gym locker room to show off his muscles, with text overlays about proving his strength and future success.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos share the exact same background music, which is a strong indicator of a causal relationship on TikTok. Additionally, both videos are centered around the theme of fitness and gym culture, with one showing a workout and the other showcasing the physical results and dedication to fitness.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it missed the identical background music as a primary linking element. While the visual content (workout vs. posing) and specific actions differ, the shared audio often signifies a direct inspiration or trend adoption. The model might have over-indexed on visual dissimilarity or different text overlays, failing to recognize the strong thematic connection within the fitness vertical, especially when driven by a shared audio track."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595460052346096914_7595599161152605447/analysis.json b/tmp/proactive_publish_20260313/7595460052346096914_7595599161152605447/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..ffbf5a63ba0426d17e6f1005537a2d0c9cd919fe
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595460052346096914_7595599161152605447/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A group of people in traditional white and blue striped costumes with large feathered hats perform a lively folk dance outdoors during the day.",
+  "投稿视频主题": "A person in a similar traditional white and blue striped costume with a large feathered hat performs an energetic folk dance at a nighttime event with a crowd, set to the same music.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos feature the same distinctive traditional dance style (Chinelo dance), identical costumes (white with blue stripes and large feathered hats), and the exact same background music, strongly indicating a direct causal relationship where the consumption video likely inspired the publish video.",
+  "model_error_analysis": "The ML model likely failed to recognize the specific cultural context of the 'Chinelo' dance, its unique costumes, and the specific traditional music. While the visual elements (costumes, dance moves) and audio are highly similar, the model might have struggled with variations in lighting (day vs. night), camera angles, and the niche nature of the traditional music, treating them as general 'dance' videos rather than a specific, causally linked cultural performance."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595474031126646034_7595640420671982904/analysis.json b/tmp/proactive_publish_20260313/7595474031126646034_7595640420671982904/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..8947e45d1a16c0b99f51fce6558830742f2879cd
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595474031126646034_7595640420671982904/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A person films from an escalator at an airport, approaching and greeting the Peruvian streamer 'Cañita' who is sitting on the floor with his luggage, while speaking about him as a top Latin American influencer.",
+  "投稿视频主题": "An animated image of a couple with crowns, labeled 'CAÑITA ❤️ OLIVIA' and 'FELIZ CAÑITITO', serves as a background for a live stream where the host (likely Cañita) interacts with his fans, mentioning 'choclitos' and 'mosquitos' (fan terms) and discussing concert tickets.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are directly centered around the Peruvian influencer 'Cañita' and his specific fan community. Video 1 shows a fan meeting Cañita at an airport, explicitly mentioning his name and status. Video 2 is a live stream using an animated graphic featuring 'Cañita' and 'Cañitito' (a term related to him), where the host interacts with his 'choclitos' and 'mosquitos' (specific fan terms). The shared specific IP and fan culture demonstrate a strong causal link.",
+  "model_error_analysis": "The ML model likely failed due to its inability to recognize the specific cultural context and niche fandom surrounding 'Cañita'. The visual styles are vastly different (real-life airport vs. animated graphic with live stream overlay), which could mislead a model relying heavily on visual features. While 'Cañita' is mentioned in text and audio, the model might not have a robust entity recognition system for this specific influencer or the semantic understanding to connect 'Cañitito', 'choclitos', and 'mosquitos' to the same fandom without deeper cultural knowledge or a comprehensive knowledge graph for internet personalities and their communities."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7595812699439648007_7604520050434854152/analysis.json b/tmp/proactive_publish_20260313/7595812699439648007_7604520050434854152/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a4816e478bfd96b688a418eb92a6233f34b6b854
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7595812699439648007_7604520050434854152/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A woman leading a worship song in a church, with other people singing along and Amharic text overlay displaying lyrics or scripture.",
+  "投稿视频主题": "A man and a woman, both wearing green shirts, sitting on a couch. The man is speaking in Amharic about faith and trusting in God, while the woman holds a Bible.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "语句文案",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos share a fine-grained thematic similarity as they both feature Christian religious content. The consumption video shows a worship service with a song and Amharic text, while the publish video features a religious teaching/sermon in Amharic, with the speakers holding a Bible. Both convey religious messages in the same language and context.",
+  "model_error_analysis": "The model likely failed to recognize the semantic and cultural connection of the religious content and language (Amharic) across different presentation formats (worship song with text vs. spoken sermon). It might have focused on superficial differences like the primary audio type (music vs. speech) or the specific actions (singing vs. speaking) rather than the underlying shared religious theme and message, which is a strong indicator of a causal relationship for a niche audience."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7597044647780764948_7604054478521748757/analysis.json b/tmp/proactive_publish_20260313/7597044647780764948_7604054478521748757/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..ed04ad42d681b621142e0d6b4f3ff389d0f114b2
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7597044647780764948_7604054478521748757/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "一个男性主播/玩家的审美剪辑，以快速剪辑和文字叠加为特色，并配有特定的背景音乐。",
+  "投稿视频主题": "一个以Minecraft角色“eggchan”和相关周边产品为主题的粉丝剪辑，采用可爱的滤镜和文字叠加，并配有与消费视频相同的背景音乐。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "两个视频都使用了完全相同的背景音乐，这是TikTok上内容创作因果关系的最强指标之一。此外，两者都采用了类似的“审美剪辑”风格，包括快速剪辑和与音乐同步的文字叠加，尽管视觉主题（真人主播与Minecraft角色）和具体滤镜效果有所不同。",
+  "model_error_analysis": "ML模型可能主要侧重于视觉内容的相似性，而这两个视频在视觉上差异巨大（一个是真人，另一个是Minecraft游戏截图和实物周边）。模型可能未能充分识别或权重相同的音频轨道作为主要的因果关联特征。此外，虽然两者都是“审美剪辑”，但其具体的视觉风格（黑暗/情绪化与明亮/可爱）差异较大，这可能导致模型在视觉层面判断为不相关。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7597788963738324232_7603763715422407957/analysis.json b/tmp/proactive_publish_20260313/7597788963738324232_7603763715422407957/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..fbcda0baef2fbe30f9cc608ef4691f1c7ec88810
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7597788963738324232_7603763715422407957/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "A person showcases various colorful replica knives, including a 'Butterfly knife' in gold, stating they are recognizable to Counter-Strike fans and available in different colors.",
+  "投稿视频主题": "Gameplay footage from a Roblox soccer game, showing players controlling avatars on a green field with game UI elements and a melancholic background song.",
+  "主题相似": "抽象主题相似",
+  "相似元素": [],
+  "reasoning": "Both videos are broadly related to gaming culture, but their specific themes are very different. Video 1 showcases physical merchandise (replica knives from Counter-Strike), while Video 2 displays gameplay from a different game (Roblox soccer). There is no direct causal link or fine-grained thematic overlap.",
+  "model_error_analysis": "The ML model likely failed to detect the relationship because the visual content, specific game titles, and nature of the content (physical merchandise vs. gameplay) are entirely different. The model might not have a robust enough 'gaming' category embedding to connect such disparate sub-genres and content types (collectible items from a shooter game vs. gameplay of a sports game on a different platform) under a single abstract theme."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7598938266598952210_7604394570947890440/analysis.json b/tmp/proactive_publish_20260313/7598938266598952210_7604394570947890440/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..16f279f4bea170d5dca330642bec33a21ea1a42e
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7598938266598952210_7604394570947890440/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A street-level view of a snowy Old Town Toronto in winter, with a rap song referencing Canadian culture playing in the background.",
+  "投稿视频主题": "A split-screen comparison of weather app screenshots showing -17°C in Downtown Toronto and 8°C in Calgary, with text overlay expressing disappointment about being in the same country.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are thematically linked by the topic of winter weather in Canada, specifically focusing on Toronto. The consumption video visually depicts a snowy Toronto street, while the publish video explicitly highlights Toronto's extreme cold weather through a weather app comparison.",
+  "model_error_analysis": "The ML model likely failed due to the significant visual and audio dissimilarity between the two videos. Video 1 is a live-action street scene with a rap soundtrack, while Video 2 is a static image of weather app screenshots with a melancholic instrumental. The connection relies on semantic understanding of location (Toronto) and weather conditions (cold winter) which are conveyed through different modalities (visuals + audio in V1 vs. text + app UI in V2). The model might not have recognized 'Toronto' as the common subject despite the different presentation formats."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7598981214132849942_7603041768992460054/analysis.json b/tmp/proactive_publish_20260313/7598981214132849942_7603041768992460054/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..eaccaf55943c6334a059520d74d452f96677d3c4
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7598981214132849942_7603041768992460054/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "一个地球仪被两罐可乐罐平衡在中间并旋转，配有“Girls: boys can't cook / Boys:”的文字和搞怪音效。",
+  "投稿视频主题": "一瓶蛋黄酱被两片面包平衡在中间并旋转，配有“women:boys cant cook / me:”的文字和相同的搞怪音效。",
+  "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": "两段视频都复刻了同一个网络迷因（meme）格式，即以“女生说男生不会做饭”为引子，然后展示男生通过平衡日常物品来“证明”自己有特殊技能。它们使用了完全相同的搞怪音效，相似的文案结构，以及相同的核心创意行为（平衡并旋转物体）。",
+  "model_error_analysis": "ML模型可能未能识别出这种特定的迷因格式。模型可能将视频中的不同物体（可乐罐/地球仪 vs. 面包/蛋黄酱）视为不相关，而忽略了它们共享的特定搞怪音效和高度相似的文本结构。此外，模型可能难以理解“平衡物体”这种抽象的创意行为是迷因的核心，而不是具体的物体本身。这需要更深层次的语义理解和跨模态（音频、文本、视觉动作）的关联能力。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7600049951300685076_7602626609417604370/analysis.json b/tmp/proactive_publish_20260313/7600049951300685076_7602626609417604370/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..13fd6097315b78eb2a106b1e78e19e886585d77d
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7600049951300685076_7602626609417604370/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A man delivers a motivational speech about the pain caused by those close to us, not enemies, with Portuguese text overlays.",
+  "投稿视频主题": "A preacher delivers a sermon on stage about the fickle nature of the crowd, referencing biblical events of Jesus being praised and then crucified, and healing paralytics.",
+  "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 the same individual delivering a religious/motivational speech. The subject (speaker) and his core action (preaching/public speaking) are identical, indicating a strong fine-grained thematic similarity within the religious/motivational content vertical.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because it might not have robust speaker recognition capabilities to identify the same person across different visual settings (close-up interview vs. stage sermon). Additionally, while both videos are spoken word, the specific phrases and background audio might be different enough to prevent an audio match. The model would need advanced semantic understanding of the spoken content to recognize the shared theme of 'religious/motivational speech' from the same individual, rather than just superficial visual or audio cues."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7600071116324900116_7602337842538368276/analysis.json b/tmp/proactive_publish_20260313/7600071116324900116_7602337842538368276/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..5750bc9f5a25d534924d974703ce62236bc0e421
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7600071116324900116_7602337842538368276/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A nail technician demonstrates the detailed process of applying gel nail extensions with a cat-eye effect on a client.",
+  "投稿视频主题": "A comedic skit shows a nail technician humorously immobilizing a client with tape and a pillow to quickly perform a nail service.",
+  "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 specific theme of professional nail services in a salon setting. Video 1 is a detailed demonstration of a nail extension process, while Video 2 is a humorous take on the client experience during a nail appointment, specifically about speeding up the process.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity due to significant differences in audio and specific actions. Video 1 uses a melancholic song and shows intricate nail work, while Video 2 uses upbeat, comedic music and features exaggerated actions of taping and pillowing a client. A model might struggle to connect these videos based on the shared fine-grained theme of 'nail salon services' when the immediate sensory inputs (audio, specific behaviors, and overall genre/mood) are so divergent and there's no shared viral audio or visual template."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7600138772541394198_7602907593710767382/analysis.json b/tmp/proactive_publish_20260313/7600138772541394198_7602907593710767382/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..4a757b0e0af3ff2040d2bc39701f9e644a2337fd
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7600138772541394198_7602907593710767382/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A man speaks directly to the camera, using the text overlay 'Worst thing she can say is no' as a setup for a comedic rant about an imagined aggressive encounter with a woman over pigeons.",
+  "投稿视频主题": "A man in headphones and a cap speaks to the camera, using the text overlay 'The worst thing she can say Is no ...' to set up a comedic, vulgar imagined scenario involving a woman named Chloe and ice skating.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "语句文案",
+    "主体行为/形态"
+  ],
+  "reasoning": "Both videos participate in the exact same viral meme format, using the identical setup phrase 'Worst thing she can say is no' (or a very slight variation) as a text overlay and spoken introduction, followed by a comedic, exaggerated, and often vulgar imagined scenario that is presented as a 'worse' outcome than a simple 'no'. This is a clear instance of a shared meme/viral format.",
+  "model_error_analysis": "The ML model likely failed to detect this causal relationship because it might not recognize the specific meme format. While the initial text overlay and spoken phrase are nearly identical, the subsequent comedic content (the 'worse' scenario) is entirely different in each video. A model might focus too heavily on the divergent content after the setup, or on visual differences (different people, different backgrounds), rather than recognizing the consistent meme structure, the shared opening phrase, and the specific comedic 'punchline' style as a template."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7600267409701833992_7604407914765290759/analysis.json b/tmp/proactive_publish_20260313/7600267409701833992_7604407914765290759/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..37189acc32bf8b2f5af34bece964ba1791b4d23f
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7600267409701833992_7604407914765290759/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A person is playing an acoustic guitar, performing a riff from 'gnaw' by Alex G.",
+  "投稿视频主题": "A person is playing an acoustic guitar and singing, performing a cover of 'go away' by Weezer.",
+  "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 individuals performing song covers on an acoustic guitar. Although the specific songs are different, the core activity of playing and covering a song on the same instrument (acoustic guitar) represents a fine-grained thematic similarity in musical performance.",
+  "model_error_analysis": "The ML model likely failed because it primarily relies on audio similarity (different songs) or exact text matches (different song titles/artists). It might not have a robust mechanism to identify the conceptual similarity of 'acoustic guitar song cover' based on visual cues of the instrument and the action of playing it, especially when the specific musical content differs."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7600717184851053846_7603923738865782037/analysis.json b/tmp/proactive_publish_20260313/7600717184851053846_7603923738865782037/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..4953be535c66f3060cada89894f3aefdd66052fb
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7600717184851053846_7603923738865782037/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "一个AI生成的猫咪家庭，讲述了猫爸爸在猫妈妈睡觉时照顾哭闹的猫宝宝，最终给猫宝宝喂酒哄睡，被猫妈妈发现后暴怒的幽默故事。",
+  "投稿视频主题": "一个AI生成的可爱猫咪穿着粉色连衣裙，在街头背景下随着音乐跳舞。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "拍摄对象"
+  ],
+  "reasoning": "两段视频都采用了高度相似的AI生成卡通猫咪形象，这些猫咪具有独特的胖胖的、拟人化的特征，并且视频中都带有“AI生成”的标签。这表明它们属于同一类AI生成内容创作的流行趋势或玩法，因此具有最强的因果关系。",
+  "model_error_analysis": "ML模型可能未能识别出“AI生成卡通猫咪”作为一种特定的内容创作趋势或“玩法”。模型可能过于关注视频中猫咪的具体行为（育儿与跳舞）和不同的背景音乐，而忽略了它们共享的独特AI视觉风格和“AI生成”这一关键标签，这些是判断它们属于同一流行格式的重要信号。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601115694347947294_7604552935992724744/analysis.json b/tmp/proactive_publish_20260313/7601115694347947294_7604552935992724744/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..e502dfe5d52f9bcde91172ccb2b617d2a2bb45fd
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601115694347947294_7604552935992724744/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A split-screen video featuring two individuals lipsyncing and dancing to a popular Russian song with a Russian text overlay.",
+  "投稿视频主题": "A video showing clips from a K-pop concert (Stray Kids) with the same popular Russian song overlaid as background music and a Russian text message to other concert-goers.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐"
+  ],
+  "reasoning": "Both videos use the exact same popular Russian song. The consumption video is a lipsync/dance trend featuring this song, and the publish video uses the same song as background music, indicating the user was inspired by the song itself, likely from seeing it in other trending videos.",
+  "model_error_analysis": "The ML model likely failed because it primarily focused on visual content and direct actions, which are very different between the two videos (lipsync/dance vs. concert footage). The crucial causal link is the identical audio track, which the model might not have weighted sufficiently, especially when the visual themes diverge. It may not recognize that using a trending song as background music for new, visually distinct content still constitutes a causal relationship in the context of TikTok trends."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601134749763030294_7602752793023204630/analysis.json b/tmp/proactive_publish_20260313/7601134749763030294_7602752793023204630/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..bea8f8e502b70b4e7ee092a1afd062a683238b52
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601134749763030294_7602752793023204630/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A nail art tutorial creating Bridgerton-themed nails, featuring overlaid clips and images of Bridgerton characters and discussing the show in Italian, set to the Bridgerton theme music.",
+  "投稿视频主题": "A screen recording of The Sims 4 gameplay, showcasing a meticulously built house that resembles the Bridgerton family residence, set to the Bridgerton theme music.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos are directly inspired by the 'Bridgerton' TV series. The consumption video creates nail art based on the show's aesthetic and characters, while the publish video recreates a prominent location from the show within a video game. The most significant causal link is the use of the identical 'Bridgerton' theme music in both videos, strongly indicating that the consumption video (or the broader Bridgerton trend it represents) inspired the publish video.",
+  "model_error_analysis": "The ML model likely failed due to the significant visual domain shift between the two videos: one is a close-up nail art tutorial, and the other is a screen recording of a video game. A model primarily relying on visual features might categorize these as 'beauty/nails' and 'gaming' respectively, missing the deeper semantic connection of the shared 'Bridgerton' IP. While both videos share the same background music, if the model's audio recognition is not robust enough for instrumental themes or if it prioritizes spoken content (present in V1, absent in V2), it might not fully leverage this strong signal. The model would need a sophisticated understanding of cultural references and IP across diverse visual contexts to correctly identify this causal link."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601312798609591574_7603019182405373206/analysis.json b/tmp/proactive_publish_20260313/7601312798609591574_7603019182405373206/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..105220dbc2214d37ba4848f187ad79a6ea990795
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601312798609591574_7603019182405373206/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A woman in a locker room dances to a Romanian song, with text overlay expressing an unbothered reaction to gossip.",
+  "投稿视频主题": "A woman in a home setting dances to the exact same Romanian song, performing similar moves, with playful emojis 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 different women performing the same specific dance choreography to the exact same popular Romanian song. This indicates a direct causal relationship where the publish video was inspired by the consumption video's format, specifically the song and associated dance.",
+  "model_error_analysis": "The ML model likely failed because it did not recognize the specific combination of the unique audio track and the corresponding dance choreography as a viral meme or challenge. It might have focused on the different subjects and backgrounds, missing the strong causal link provided by the identical music and highly similar specific dance moves. The absence of identical text overlays in the publish video compared to the consumption video might also have contributed to the model's misclassification."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601325066151890196_7602212400758000916/analysis.json b/tmp/proactive_publish_20260313/7601325066151890196_7602212400758000916/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..4c701c90ed37f33bac4e5f5deb9e9e2d34c53eda
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601325066151890196_7602212400758000916/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "一位女性对着镜头，伴随着快节奏的音乐进行唇语对口型表演，并做出各种面部表情和手势。",
+  "投稿视频主题": "一位年轻女性在镜子前用手机自拍，伴随着与消费视频相同的快节奏音乐进行唇语对口型表演，并做出相似的表情和动作。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "主体行为/形态"
+  ],
+  "reasoning": "两段视频都使用了完全相同的背景音乐，并且视频中的人物都伴随着音乐进行唇语对口型表演，动作和表情也高度相似，这表明投稿视频是受消费视频启发而创作的。",
+  "model_error_analysis": "ML模型可能未能识别出这两段视频的因果关系，主要是因为它可能没有充分识别或权重化视频之间完全相同的背景音乐。尽管视频中的人物、拍摄环境和拍摄方式（直拍与镜面自拍）存在视觉差异，但相同的音乐和由此引发的相似唇语表演是强烈的因果信号，模型可能过度关注了视觉上的不同而忽略了核心的音频和行为模式相似性。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601574274960231702_7602694663203523862/analysis.json b/tmp/proactive_publish_20260313/7601574274960231702_7602694663203523862/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..80dfbbb14a6b8fc0fa8306452d44917da4f84e7e
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601574274960231702_7602694663203523862/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A woman lipsyncs to the intro of a K-pop song, with text overlay stating that the song reminds her of Jungwon.",
+  "投稿视频主题": "A woman sits and expresses emotions to the same K-pop song, with text overlay stating that the song feels like Jungwon with angel wings.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos use the exact same K-pop song and explicitly mention the same K-pop idol, Jungwon, in their text overlays, associating him with the song. This indicates a direct causal relationship based on a shared specific fan sentiment and audio.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship due to several factors. It might have struggled to recognize the 'same song' if it only analyzed short audio segments, as the consumption video features the song's intro while the publish video features a later part. Crucially, the model probably missed the strong semantic connection in the text overlays, where both videos explicitly mention the specific K-pop idol 'Jungwon' in relation to the song. This requires robust OCR and natural language understanding to identify the shared niche fan sentiment or 'meme' that links the two videos, which a typical audio or visual similarity model might overlook."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601579424177343762_7602468045705006356/analysis.json b/tmp/proactive_publish_20260313/7601579424177343762_7602468045705006356/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..b9b104aabeea0d026d4e4b470e950bb0fc65d69a
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601579424177343762_7602468045705006356/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A screen recording showing a Roblox avatar dancing in a split-screen TikTok video with a trending audio and Portuguese text overlay, while browsing Roblox customization options.",
+  "投稿视频主题": "A screen recording of a user creating a TikTok video using various animated stickers and effects, with the same trending audio and a Portuguese caption.",
+  "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 trending audio, which includes both music and spoken phrases. The reuse of a specific, recognizable audio track is a strong indicator of a causal relationship, as it often signifies participation in the same viral trend or meme.",
+  "model_error_analysis": "The ML model likely failed to detect the similarity because it may not have a robust audio fingerprinting mechanism to identify identical trending audio across different videos. The visual content of the two videos is quite distinct (Roblox avatar customization vs. TikTok editing interface with animated stickers), which could have led the model to incorrectly classify them as unrelated if it primarily relies on visual features rather than audio as a primary causal link for trends."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601586470712954115_7603338240136908054/analysis.json b/tmp/proactive_publish_20260313/7601586470712954115_7603338240136908054/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..78d49032cf59773e8a346e5ad771d77a4c8f748f
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601586470712954115_7603338240136908054/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "A person's hand gently pets a small, sleepy black kitten on a yellow background.",
+  "投稿视频主题": "A black and white cat sits on a chair, appearing to 'call for help' with its gaze as a toddler repeatedly tries to interact with it.",
+  "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 as the main subject. Video 1 shows a cute kitten being petted, while Video 2 humorously depicts a cat's interaction with a toddler. They share a fine-grained thematic similarity around 'pet cats'.",
+  "model_error_analysis": "The ML model likely failed because it focused on the distinct narratives and specific scenarios rather than the overarching fine-grained theme of 'pet cats'. The cats are different (kitten vs. adult), the actions are different (gentle petting vs. toddler interaction), and the audio/text overlays are unique to each video. The model might not have generalized the 'cat' subject sufficiently across these different contexts and narratives to identify the thematic similarity."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601669855993007382_7603430768756477206/analysis.json b/tmp/proactive_publish_20260313/7601669855993007382_7603430768756477206/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..5dd1662464561a2901364778c4fecdc3ed6cefc0
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601669855993007382_7603430768756477206/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A woman in a pink robe holds and gently bounces a baby to a rhythmic electronic music track, with a text overlay about diaper changes.",
+  "投稿视频主题": "A toddler sits on a playmat, playing with a toy, synchronized to the same rhythmic electronic music track, with a spoken phrase about a battery being recharged.",
+  "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 distinctive electronic music track, which is part of a viral audio trend. The actions in both videos are synchronized with the music, and the text/spoken audio in each video relates to the narrative context of this specific meme (e.g., 'back to square one' or 'recharged').",
+  "model_error_analysis": "The ML model likely failed to identify the specific audio as a viral trend or meme. It might have focused on the disparate visual content (woman with baby vs. toddler with toy) and different literal text overlays, missing the underlying causal link established by the shared, highly recognizable audio and the synchronized actions that are characteristic of this meme format. The model needs to understand that specific audio tracks can define a '玩法' (viral format) even if visual subjects differ."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601674006034402582_7602604985834048790/analysis.json b/tmp/proactive_publish_20260313/7601674006034402582_7602604985834048790/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a7c655849a1092983a918ff14158bf7f956f6cc1
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601674006034402582_7602604985834048790/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "视频展示了夜空中绽放的烟花，并配有意大利语歌词作为文字叠加。",
+  "投稿视频主题": "视频中一位年轻女子在车内自拍，她对着镜头，并配有与消费视频相同的意大利语歌词作为文字叠加。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "两个视频使用了完全相同的背景音乐，并且投稿视频的文字叠加包含了消费视频中的核心歌词。这表明投稿视频直接受到了消费视频中音乐和歌词内容的启发，属于因果性最强的主题相似。",
+  "model_error_analysis": "ML模型可能未能识别出这种因果关系，因为它可能过度依赖视觉内容进行判断。消费视频是烟花，而投稿视频是人物自拍，视觉上差异巨大。模型可能未能有效关联意大利语的文字叠加与背景音乐的歌词，或者未能将这种“使用特定歌曲及其歌词作为情感表达”的模式识别为一种可复用的TikTok内容格式或模因，从而错判为不相关。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601713212869856533_7602376124693351688/analysis.json b/tmp/proactive_publish_20260313/7601713212869856533_7602376124693351688/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..c74c12d70dde5b065ad156d446eaa39d1b932151
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601713212869856533_7602376124693351688/analysis.json
@@ -0,0 +1,8 @@
+{
+  "消费视频主题": "一个AI生成的Winx Club角色在森林背景下跳舞，配有巴西放克音乐。",
+  "投稿视频主题": "一个动画角色施展魔法创造出一只小狗，并配有葡萄牙语对话。",
+  "主题相似": "抽象主题相似",
+  "相似元素": [],
+  "reasoning": "两个视频都以动画角色为主题，但角色IP、动画风格、背景音乐、对话内容和主体行为都完全不同。它们唯一的共同点是都属于动画内容这一大类。",
+  "model_error_analysis": "ML模型可能未能识别出这种抽象的主题相似性，因为它缺乏具体的、低级别的特征重叠，例如相同的音乐、视觉模板、特定动作或文本。模型可能更侧重于检测直接的因果关系信号，而这两个视频之间只有非常宽泛的“动画”这一共同点，这对于模型来说很难捕捉。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601765261200461078_7602681205758102806/analysis.json b/tmp/proactive_publish_20260313/7601765261200461078_7602681205758102806/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..f3a9cde1224e7d6dc66456f02c72f200f19df22a
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601765261200461078_7602681205758102806/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A close-up video of a cute baby making various facial expressions, set to a non-English song with text overlay.",
+  "投稿视频主题": "A slideshow of photos featuring a cute baby in different outfits and poses, set to the exact same non-English song.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature a cute baby and use the exact same background music. The consumption video likely inspired the publish video to use this specific trending audio with similar content (a cute baby).",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might not have a strong audio matching component or might not prioritize shared background music as a primary signal for causation, especially when the visual format differs (single video clip vs. photo slideshow). The model might have focused too much on visual differences in presentation rather than the strong, explicit link provided by the identical audio track."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601949430056602900_7602434611599265044/analysis.json b/tmp/proactive_publish_20260313/7601949430056602900_7602434611599265044/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..a8cc04dfa8bb60b6ae75419057587a94f743ec04
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601949430056602900_7602434611599265044/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "Two women with brightly colored hair (pink/red) are shown dancing and posing in a studio before a live stream, then joined by two men, illustrating a 'before and after' scenario of the live event.",
+  "投稿视频主题": "A young woman uses a split-screen template with four photos of herself, asking if her mother will allow her to dye her hair pink, with options for 'allowed', 'not allowed', 'will think', and 'maybe'.",
+  "主题相似": "细粒度主题相似",
+  "相似元素": [
+    "拍摄对象"
+  ],
+  "reasoning": "The consumption video features individuals with prominent pink/red hair. The publish video directly addresses the user's desire to dye her hair pink, making the specific topic of 'pink hair' a fine-grained thematic connection between the two videos.",
+  "model_error_analysis": "The ML model likely failed to detect this similarity because it requires a nuanced understanding of visual attributes (pink hair in video 1) and their semantic connection to explicit textual content (asking to dye hair pink in video 2). The model might have focused on the primary actions (dancing/live stream vs. poll/decision) or different audio tracks, missing the specific shared interest in hair color, which is not a direct meme, audio, or visual template match."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601970606141148438_7603078990038895894/analysis.json b/tmp/proactive_publish_20260313/7601970606141148438_7603078990038895894/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..518a0444bbbd76f8d6a6496a4ded503d693a388e
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601970606141148438_7603078990038895894/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "Two young women perform a synchronized dance in a kitchen, with text overlay about friends who don't dance.",
+  "投稿视频主题": "A group of people dance at a nighttime party, seen through a window, with the same text overlay about friends who don't dance.",
+  "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 viral audio and text overlay, which is a direct quote from the song. This indicates a strong causal link, as the publish video is clearly inspired by or participating in the same specific TikTok trend/meme.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it might have focused too much on visual dissimilarities (different settings, number of people, specific dance moves, lighting conditions). It probably did not effectively combine the strong signals from the identical audio and text overlay to recognize that both videos are participating in the exact same viral meme/trend, which is defined by this specific audio-text combination rather than visual choreography or setting."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7601998610477190422_7602715371820338454/analysis.json b/tmp/proactive_publish_20260313/7601998610477190422_7602715371820338454/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..960a3b8582bd9145f767ef92d2f06b4d046036a9
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7601998610477190422_7602715371820338454/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A highly stylized music video featuring dramatic natural landscapes like mountains, waterfalls, and oceans, with Polish lyrical text overlays.",
+  "投稿视频主题": "A POV video from inside a car driving in snowy traffic, with a Polish lyrical text overlay 'Serce wciąż oddycha tu...' (My heart still breathes here...).",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "The publish video uses the exact same Polish song as the consumption video. Additionally, the text overlay in the publish video is a direct lyric from the song featured in the consumption video, indicating a strong causal relationship.",
+  "model_error_analysis": "The ML model likely failed to detect the causal relationship because it primarily focused on visual content, which is vastly different between the two videos (stylized nature scenes vs. car interior/traffic). It probably did not adequately weigh the strong multimodal signals of identical background music and a direct lyrical text match, especially given the Polish language content which might pose challenges for cross-lingual audio-text matching or lyric extraction."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602006928537046280_7602420413976546567/analysis.json b/tmp/proactive_publish_20260313/7602006928537046280_7602420413976546567/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..7bd9d6504435dd3f46b3ba85064bbf8a00ded869
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602006928537046280_7602420413976546567/analysis.json
@@ -0,0 +1,12 @@
+{
+  "消费视频主题": "A young woman poses in a dimly lit setting with red lighting, featuring a text overlay about wanting to be memorable like a guitar solo, set to an instrumental track.",
+  "投稿视频主题": "A young woman poses in a dimly lit setting with blue lighting, featuring the identical text overlay about wanting to be memorable like a guitar solo, set to the same instrumental track.",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "画风呈现",
+    "音乐",
+    "语句文案"
+  ],
+  "reasoning": "Both videos use the exact same trending audio and text overlay, following a clear meme format where a person poses in a dimly lit environment while the specific audio and text convey a message about being memorable. This indicates a direct causal relationship.",
+  "model_error_analysis": "The ML model likely failed to recognize the strong causal link because it did not adequately weigh the identical audio and text overlay as key indicators of a shared meme or viral format. It might have focused too much on superficial visual differences, such as the different individuals and varying lighting colors, rather than the consistent template of a moody selfie with specific audio and text."
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602009271491988743_7604143486912171271/analysis.json b/tmp/proactive_publish_20260313/7602009271491988743_7604143486912171271/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..1a9e10cc8bc6abc90454704f86d61d4fde8c0389
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602009271491988743_7604143486912171271/analysis.json
@@ -0,0 +1,10 @@
+{
+  "消费视频主题": "该视频展示了青少年美式橄榄球比赛和冰上滑冰的片段，并配有法文叠加文本，询问如果回答是“是”，问题会是什么。",
+  "投稿视频主题": "该视频展示了《堡垒之夜》游戏大厅的屏幕，用户查看了朋友“Ryningan”的离线状态，并配有法文叠加文本，表达了对一位突然离去的朋友的悲伤。",
+  "主题相似": "最具因果性",
+  "相似元素": [
+    "音乐"
+  ],
+  "reasoning": "两个视频都使用了完全相同的背景音乐，这首音乐传达了一种忧郁或反思的情绪。尽管视觉内容和具体的文本叠加不同，但共享的音乐强烈表明它们遵循了同一个情感主题或音频趋势。",
+  "model_error_analysis": "ML模型可能主要关注视频的视觉内容和文本，而未能充分识别背景音乐作为视频主题或趋势驱动因素的重要性。由于两个视频的视觉内容（体育/滑冰与游戏）完全不相关，模型可能因此判断它们不相似，而忽略了作为核心相似元素的共享音频。"
+}
\ No newline at end of file
diff --git a/tmp/proactive_publish_20260313/7602060282625674517_7602477809264495880/analysis.json b/tmp/proactive_publish_20260313/7602060282625674517_7602477809264495880/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..9fbe38ea567a94beb0b57d8e563d9797d80f198c
--- /dev/null
+++ b/tmp/proactive_publish_20260313/7602060282625674517_7602477809264495880/analysis.json
@@ -0,0 +1,11 @@
+{
+  "消费视频主题": "A streamer (Gabepeixe) recounts his experience of taking 'sleep water' (melatonin) and its strong sedative effects, while another streamer (Loud Coringa) reacts to the story in a split-screen format.",
+  "投稿视频主题": "A streamer (Loud Coringa) reacts to a fan-made TikTok edit featuring himself and two other streamers (Brabox and Gabepeixe), highlighting them as 'the 3 best on Twitch,' presented in a split-screen format.",
+  "主题相似": "抽象主题相似",
+  "相似元素": [
+    "画风呈现",
+    "拍摄对象"
+  ],
+  "reasoning": "Both videos feature the streamer Loud Coringa reacting to content in a split-screen format. The consumption video shows him reacting to a personal anecdote involving another streamer, Gabepeixe. The publish video shows him reacting to a fan edit featuring himself, Gabepeixe, and Brabox. The shared subjects (streamers) and the split-screen reaction format indicate an abstract thematic similarity.",
+  "model_error_analysis": "The ML model likely failed because it focused on the specific content being reacted to (melatonin story vs. fan edit about 'best streamers'), which are distinct topics. It might have missed the broader context of 'streamer reaction content' and the recurring individuals (Loud Coringa, Gabepeixe, Brabox) as a unifying theme. The model may also not have adequately captured the 'split-screen reaction' as a shared visual style/presentation, leading to a misclassification of irrelevance."
+}
\ No newline at end of file