The quant team has invested a significant amount of data science work in anti-witch hunting screening—employing techniques such as clustering analysis, behavior pattern recognition, and more. This plan also involved the participation of several senior protocols and well-known on-chain data analysts in the design process, making the final results quite reliable. Of course, if misjudgments still occur, users can fully file a complaint. In the long run, the relevant responsible persons emphasize that all value will ultimately be reflected at the token level, which is also the project's core commitment to ecosystem development.

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GetRichLeekvip
· 10h ago
Listen, buddy, clustering analysis, behavior pattern recognition... all these buzzwords and you still can't find my alt account, lol.
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SchrodingersPapervip
· 10h ago
Data science, clustering analysis, behavior recognition... Just hearing these words feels like they're describing my trading records haha. Anyway, witch screening stuff—no matter how nicely it's said, it's still a knife that cuts.
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MerkleTreeHuggervip
· 10h ago
Hmm... that clustering analysis stuff, can it really filter out witches? I'm still a bit skeptical.
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PrivacyMaximalistvip
· 10h ago
Is the misjudgment appeal process really reliable? I'll have to wait in line for review again...
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CodeSmellHuntervip
· 10h ago
Data science sounds pretty impressive, but how likely is it to actually catch the witch?
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ForkLibertarianvip
· 10h ago
I think, when it comes to the misjudgment appeal process, the key still depends on how it is implemented in practice. Just talking about nice words doesn't cut it.
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