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Beyond Answer Confidence: A Controlled Audit of Self-Knowledge in a Black-Box Decision Model
Decision models return probabilities intended for routing, abstention and automated action. Calibration makes those probabilities useful on average, but does not establish whether low confidence reflects chance or missing knowledge, nor whether confidence falls when a model moves beyond what it know
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