Unverified60% confidenceOpinionExact time
Errors in confidence scoring systems are distributed across the entire score range, manifesting as calibration error—high in coverage but difficult to detect.
2
Sources
60%
Confidence
Long-term
Relevance
8/4/2026
First Seen
Sources
置信度评分vs二元规则匹配:AI系统该如何选择
redditr/LanguageTechnology8/3/2026
Related Claims
UnverifiedOn out-of-distribution inputs, high-confidence erroneous judgments are quite common.79% similarUnverifiedWhen different raters understand the same level very differently, the Likert scale leads to unstable inter-rater reliability, and a single number cannot carry information about specific good and bad dimensions.78% similarUnverifiedBias introduced by a single defective data point can leak into seemingly unrelated capability dimensions, causing the model to simultaneously regress across multiple independent metrics such as deceptiveness, compliance, and risk aversion.77% similarUnverifiedThe overconfidence of a model answering directly while skipping retrieval is technically referred to as miscalibration, meaning there is a systematic deviation between confidence and actual accuracy.76% similarUnverifiedOn the low-error-rate subset, representational consensus did not outperform paraphrase consensus and instead produced significantly more false positives.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/685445API
curl https://kongchang.com/api/v1/knowledge/claims/685445MCP
get_claim(id=685445)