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This study evaluated the references OE returned to 150 standardized prompts across five specialties, analyzing all 4979 citations and found most references were recent and high-impact, though journal concentration varied by specialty.
Routine reporting of calibration and uncertainty and measurement of end-to-end clinical performance are prerequisites for responsible SLM deployment.
Current evidence does not support the use of LLMs for diagnosis, treatment selection, or patient education in AD/MCI without clinician oversight, and are further limited by small heterogeneous evaluations, sparse hallucination measurement, and absence of prospective clinical validation.
Under this benchmark, OpenEvidence produced fewer missed emergencies than the historical ChatGPT Health comparison, while errors concentrated in over-triage and evidence-seeking refusal.
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