ORES review tool/it

The ORES review tool is the key user-facing feature of the ORES extension, which provides objective revision evaluation services to automatically rate a revision's characteristics: likelihood it is vandalism, degree to which it might be damaging, likelihood of being good faith, likelihood it will be reverted, and overall quality. The review interface integrates the scores generated by the ORES service into MediaWiki's interface. ORES provides automated scoring of revisions in order to aid editors. For example, ORES can predict whether or not an edit is vandalism, as well as the overall quality level of an article. See ORES' documentation for more information about what types of scoring are available.

The default threshold is deliberately set low to capture almost all vandalism cases (so a number of false positives are also likely to occur). This is in contrast to anti-vandalism bots which set the threshold high to capture only the most obvious vandalism cases (and thus have few false positives). If you do not want to see the flag for most edits, you can simply change ORES sensitivity (see below).

Usare ORES
If the ORES extension is activated, you can enable the review tool within your user account by looking under the "beta features" section of Special:Preferences. The review tool will augment Special:RecentChanges and Special:Watchlist by highlighting and flagging edits (with a red-colored r ) that need review, because the ORES prediction model judges them to be "damaging". You will also be able to filter these lists by selecting the "Hide good edits" option. When you select this option, the review tool will hide any edits that ORES judges to be unlikely to be damaging. If you review an edit and realize it is not vandalism, you can simply mark it as "patrolled", and the highlighting and flag will be removed.

You can change the sensitivity of ORES in your preferences (under the "Recent changes" tab) to "High (flags more edits)" or "Low (flags fewer edits)". You can also choose to make "Hide good edits" selected by default.



How does ORES detect damaging edits?
ORES uses machine learning strategies to "learn" what damaging edits look like, by reviewing examples created by Wikipedians through Wiki labels. These predictions are inherently imperfect because ORES cannot be as smart as an experienced human editor. However, ORES can help make the work of RecentChanges-patrolling easier by flagging edits that might be damaging. This is why the review interface states that flagged edits "may be damaging and should be reviewed". Ultimately, human editorial judgement is necessary for determining which edits are damaging and which edits are not.

See m:Objective Revision Evaluation Service for more information about how "edit quality" is evaluated in ORES.

Why use the term "damaging" instead of "vandalism"?
"Vandalism" is just a subset of what we want to catch when we're doing RC Patrolling. The word "vandalism" implies deliberate malicious intent. However, a patroller's job is to look for damaging edits whether the damage was actually intended or not. Therefore, referring to the edits that the review tool flags as "damaging" is more true to the kind of work the system is designed to support.

Look for dameges