Rohan Paul· @rohanpaul_ai · X·· 2 小时前AI 评分65
AI 导读
一项新预印本测试了 15 个模型在临床试验论文中查找植入错误的能力，得分区间为 53% 到 96%，而未受训练的人类审稿人平均只有 27%。该结果在 2026 年发表的 58 项新试验上依然成立，说明模型并非只是回忆训练中见过的旧论文，其中 Claude Opus 5.5 得分最高，为 99%。
正文
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.
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 🧵在 X 查看被引用的帖子
来源：Rohan Paul · x.com