ScholScan (Text Input) - Inference and Conclusions: leaderboard

Metric: Flaw-detection score (0-1, scaled to 0-100): per question, zero unless the model finds the annotated scientific error, otherwise the geometric mean of evidence-location Dice and reasoning-chain prefix match, times a penalty for unrelated errors listed, as extracted by a GPT-4.1 evaluator, averaged over the inference and conclusions questions of ScholScan's 1,800 expert-reviewed questions that ask a model to scan a whole academic paper (ICLR 2024-2025 and Nature Communications, 715 papers) for a planted or reviewer-reported scientific flaw without being told where to look, with the paper given as Tesseract OCR text; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 15 models tracked.

Top models

#ModelScoreOverall rank
1GPT-529.8#91
2Gemini 2.5 Pro28.8#145
3Seed-1.620.1#257
4Grok 420#169
5Doubao-Seed-1.6 (Thinking)19.2
6DeepSeek R116.3#245
7GPT-OSS-120B12.5#330
8Claude Sonnet 48.4#194
9Gemma 3 27B7.7#596
10Llama 4 Maverick5.8#451
11Mistral Small 3.14#600
12DeepSeek V3.12.2#260

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=scholscan-text-input-inference-and-conclusions · How It Works · Data refreshed daily, snapshot 2026-10-11.