Help:New filters for edit review/Quality and Intent Filters

Predictions are based on ORES review tool, using good faith and damaging models. Only wikis with those models will have access to the predictions filters.

How to use the filters
Those prediction filters are working like the default filters. See the main Filters page.

It is possible to use highlighting with the prediction filters as well. See the page concerning Highlighting.

Conflicts with prediction filters
There is a conflict between Logged Actions or Wikidata Edits and any prediction filter. Logged Actions are not scored by ORES, and the ORES extension does not yet handle propagated Wikidata Edits. Thus if the user selects either or both of these filters (and no other filter in the Type of Change group) along with any combination of Intent or Quality (ORES) filters, then the filters cancel each other out.

No results will be displayed and the two conflicting filters will turn red with an explanation message.

Contribution quality predictions
Filter edits based on predictions about their quality. These predictions are made by ORES, a machine-learning service trained on a large set of edits previously scored by human editors.

Filters with different levels of accuracy are provided. Stricter, more accurate filters find fewer false positives, but they return fewer results overall. Less accurate filters cast a wider net and find more of their target, but they also find more false positives.

Very likely good

Highly accurate at finding almost all problem-free edits.

May have problems

Finds most flawed or damaging edits but with lower accuracy.

Likely have problems

Finds half of flawed or damaging edits with medium accuracy.

Very likely have problems

Highly accurate at finding the most obvious 10% of flawed or damaging edits.

User intent predictions
Filter edits based on predictions that the editors were, or weren't, in good-faith. These predictions come from ORES, a machine-learning service trained on a large set of edits previously scored by human editors.

Filters with different levels of accuracy are provided. Stricter, more accurate filters find fewer false positives, but they return fewer results overall. Less accurate filters cast a wider net and find more of their target, but they also find more false positives.

Very likely good faith

Highly accurate at finding almost all good-faith edits.

May be bad faith

Finds most bad-faith edits but with a lower accuracy.

Likely bad faith

With medium accuracy, finds the most obvious obvious 25% of bad-faith edits.