Sebastian Fox examines production clinical-note failures that can look acceptable to generic evaluators while omitting symptoms, adding unsupported diagnoses or medications, or missing a clinician's final decision. These errors show why surface-level accuracy scores are not enough in high-stakes medical workflows.
Sebastian Fox proposes discovering failure modes from real outputs instead of guessing them in advance. Domain experts should label what went wrong and explain the relevant clinical judgment so evaluation criteria reflect the consequences of each case.
The resulting evaluation loop should retrieve similar cases, current guidance and prior expert corrections for every new output. Because medical standards and model behavior both change, the checks must be continuously recalibrated rather than frozen into one static rubric.
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