Unverified50% confidenceFactExact time
A calibration curve can be used to check whether the model's self-reported confidence matches its actual accuracy; an 'overconfident' model will let incorrect answers through even with a reasonable threshold setting.
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50%
Confidence
Long-term
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11/2/2026
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VerifiedCalibration is typically visualized using a reliability diagram (calibration curve), with confidence on the horizontal axis and the actual accuracy of samples in that interval on the vertical axis.73% similarUnverifiedA confidence score is the model's quantitative assessment of the reliability of its own answer, usually generated by the model or computed by an additional model; a low confidence score can trigger human review or a downgraded response to avoid error propagation.73% similarUnverifiedCalibration of the response decision refers to the degree of match between the model's confidence in its binary judgment of 'whether to act' and the actual accuracy.72% similarUnverifiedWhen the true effect cannot be directly verified, a round of A/A testing can be run on candidate causal models first, and then the model to trust can be determined based on estimation error.69% similarUnverified校准性（Calibration）指模型表达的置信度与实际准确率之间的一致程度，是评估AI模型质量的核心指标之一68% similar
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