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Impressive accuracy. The real value here is the feedback loop—using automated discovery to validate signals against real-world drift. Are you tracking the decay rate on these outliers too?

Not yet. Right now each item gets one re-check a week later, that’s this post.

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That’s a solid MVP start. If you log those re-checks, you can calculate the drift velocity over time. It transforms a simple re-check into a predictive signal for model retraining. Are you flagging the "stable" ones to reduce future compute?