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I've been using decibels as a scale for log-odds for a while when reporting results. It works pretty well, since the relevant part of the scale is wide, unlike using nepers, which I had never heard of until I started noodling around with this.

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Like, how many decibels of evidence does this observation provide for this hypothesis? That seems potentially pretty workable, as long as you can ensure conditional independence.

Yes. For like a simple naive Bayes, you can say we start at 0, a user vote is worth +3, a merchant vote is +5, we decay by 0.1 every month, publish if we hit +13 (95%), un-publish at +10 (90%), etc. etc.

It's the same math as logits, but the scale's a bit nicer.

Thanks! I didn't realize you'd been doing that kind of thing lately.

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