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Routine reporting of calibration and uncertainty and measurement of end-to-end clinical performance are prerequisites for responsible SLM deployment.
Before AI-assisted triage enters rheumatology referral pathways, systems should separate objective clinical evidence from interpretive framing, and urgency and psychological attribution should be treated as auditable safety signals.
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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