Actually, we openly report a wide variety of statistics about our models.  E.g. if you go to <a href="https:&#x2F;&#x2F;ores.wmflabs.org&#x2F;scores&#x2F;enwiki" rel="nofollow">https:&#x2F;&#x2F;ores.wmflabs.org&#x2F;scores&#x2F;enwiki</a>, the service lists out the models that are available for English Wikipedia along with test statistics.  You can also browse our test statistics in our documentation.  See <a href="https:&#x2F;&#x2F;meta.wikimedia.org&#x2F;wiki&#x2F;ORES&#x2F;damaging#English_Wikipedia_.28enwiki.29" rel="nofollow">https:&#x2F;&#x2F;meta.wikimedia.org&#x2F;wiki&#x2F;ORES&#x2F;damaging#English_Wikipe...</a><p>Currently, we&#x27;re optimizing for AUC since it (1) is hard to cheat -- unlike accuracy or precision&#x2F;recall individually and (2) it represents the ranking problem well.<p>See <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Receiver_operating_characteristic#Area_under_the_curve" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Receiver_operating_characteris...</a><p>&quot;[AUC] is equal to the probability that a classifier will rank a randomly chosen positive instance higher than a randomly chosen negative one&quot;