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[Investigate] Wikidata revert model's precision and recall (filter rate)
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Question: What proportion of human-edits will need to be reviewed if we want 95% recall?


  1. Gather random sample of edits
  2. Label reverted
  3. Explore dataset of non-reverted damage

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Started some work here. This is based off of a random sample of wikidata edits

OK. If we draw the cutoff at 0.93, we'll catch 100/10000 edits and that will account for (as far as we can tell) all of the vandalism!

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