What does categorical cross-entropy primarily measure for a multiclass classifier?

The correct answer is: How well predicted class probabilities match the true one-hot labels. This matches standard ML/AI engineering practice for Domain 2: Evaluation. Distractors confuse adjacent concepts or unsafe operational shortcuts. In production, validate with held-out data, monitoring, and governance appropriate to risk.