False negative

A missed positive case: the system predicts negative when the reference says positive.

The positive class must be stated. If positive means an annotation error, a false negative is an error the review failed to flag. If positive means acceptable data, the same phrase describes a different mistake. Naming the actual failure makes review reports easier to interpret.

In practice

With error as the positive class, an incorrect success label that passes review is a false negative.