An attribution classifier has 95% precision on a benchm...

The issue is a mismatch between the benchmark’s construction and the production environment. Because the benchmark’s ground-truth documents are all genuine, the classifier never learned to distinguish between authentic sources and fabrications. The solution is to implement an authenticity gate rather than retraining the classifier on more attribution labels, as the latter does not address the underlying failure mode.