PSEBench - Uncertainty Detection: leaderboard

A PSEBench patient safety triage dimension: the binary F1 of escalating irreducibly ambiguous gray-zone events to the Uncertain verdict, in percent; higher is better. PSEBench (2026) builds 5,074 verifiable cases from clause cards of the Minnesota 29 reportable adverse health events, and models may query a simulated information provider before answering.

Metric: Uncertain detection F1 (%, M7): binary F1 of routing gray-zone cases to the Uncertain verdict, over all cases, on the 5,074-case MN29 benchmark (3,455 complete, 1,362 missing-information and 257 uncertain cases built from clause cards of the Minnesota 29 reportable adverse health events), agentic environment where the model may ASK a GPT-5.2 information provider within 10 turns and then answers with a verdict, clause, legal evidence and rationale; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 15 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.579.7#49
2Gemini 3.1 Pro (Preview)74#94
3Claude Opus 4.757.1#79
4Claude Sonnet 4.649.2#161
5DeepSeek R136.3#473
6Gemini 2.5 Flash31.3#453
7Qwen 3 235B A22B 2507 Instruct18.3#619
8GPT-512.8#167
9Llama 3.1 8B Instruct10.5#4246
10GPT-5 Nano10.1#889
11GPT-OSS-120B10#700
12Mistral Small 3.22.2#1591

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=psebench-uncertainty-detection · How It Works · Data refreshed daily, snapshot 2026-11-13.