Rohan Paul· @rohanpaul_ai · X·· 20 小时前AI 评分68
AI 导读
一项新预印本测试了 15 个 LLM 检测临床试验论文中植入方法学错误的能力，模型得分 53% 到 96%，而未受训练的人类审稿人平均仅 27%。在 58 项 2026 年发表的新试验上结果仍成立，Claude Opus 5.5 最高达 99%；人类仅 7% 的情况下能发现文本与表格矛盾，每篇审稿需 5 到 8.5 小时，AI 只需 1.4 到 16.3 分钟。
正文 · 原文
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