ScholScan (Text Input) - Research Question and Definitions: 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 research question and definitions 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 August 2027. 15 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro21.5#145
2GPT-516.1#91
3Grok 49.3#169
4Doubao-Seed-1.6 (Thinking)8.2
5GPT-OSS-120B6.3#330
6Seed-1.65.4#257
7DeepSeek R15.1#245
8Claude Sonnet 43.7#194
9Mistral Small 3.13#600
10Gemma 3 27B2.1#596
11Llama 4 Maverick1.5#451
12DeepSeek V3.11.2#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-research-question-and-definitions · How It Works · Data refreshed daily, snapshot 2026-10-11.