Health benchmarks usually refer to evaluating a model's level of medical knowledge using standardized medical question-answering datasets (such as MedQA, PubMedQA, etc.), with accuracy as the main metric; such tests assume by default that the model should try to give an answer, but Tabibu's safety layer actively refuses diagnosis and so on, causing many questions it could have answered correctly to be intercepted by safety fallbacks.