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Rohan Paul· @rohanpaul_ai · X· · Original publication time SelectedAI score60

Preprint compares AI and human error detection in clinical trial papersMachine translation

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A preprint reports that 15 AI models caught 53%–96% of planted errors, versus an average of 27% for untrained human reviewers. On 58 newly published clinical trials from 2026, Claude Opus 5.5 scored highest at 99%. These are results reported in a preprint.

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@rohanpaul_ai

> AI now catches far more errors in clinical trial papers than human peer reviewers: all 15 models tested scored 53% to 96% on planted errors, while untrained human reviewers averaged just 27%.

> The result held on 58 new trials published in 2026, so the models weren’t simply recalling old papers they had seen in training; Claude Opus 5.5 scored highest at 99%.

> Humans miss the errors that most change a trial’s meaning, catching text-table contradictions only 7% of the time, and they take 5 to 8.5 hours per review against AI’s 1.4 to 16.3 minutes.

QuoteRuslan Rust@rust_ruslan
Lots of debate this week on whether journals should ban AI in peer review. We actually tested this in our new preprint, and the results were pretty clear to me. For context, I've reviewed for most of the big journals and evaluated 1,000 human reviews as an editor. I love to read and evaluate science. TLDR: From now on I won't do any peer review without AI. For clinical trials, I'd even call human-only review dangerous 🧵
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