人工智能时代的同行评审:对人类和人工智能生成的评审报告进行比较研究
Hamrish Kumar Rajakumar1, Kailash Abhishek Sankaran1, Manasi Pillai Ashok1
1Government Medical College, Omandurar Government Estate, 169, Wallahjah Road, Police Quarters, Triplicane, Chennai, Tamilnadu - 600 002, India.
Postgraduate medical journal
|January 27, 2026
概括
人类同行评审提供了比人工智能生成的报告更有洞察力和多样化的反. 虽然人工智能可以协助进行基本检查,但人类的专业知识仍然对批判性科学评估和确保同行评审的质量至关重要.
科学领域:
- 图书统计学 图书统计学
- 科学出版科学出版
- 研究中的人工智能.
背景情况:
- 越来越多的科学出版物给传统的同行评审系统带来了压力.
- 生成型人工智能 (AI) 提出了支持同行评审过程的潜在解决方案.
- 这项研究评估了人写与人工智能生成的同行评审报告的比较质量.
研究的目的:
- 将人类撰写的同行评审报告的专题多样性和深度与人工智能生成的报告进行比较.
- 评估AI在识别关键科学问题的表现,而不是常规结构元素.
主要方法:
- 分析了BMJ Open发表的119篇研究文章中的398篇同行评审报告.
- 使用ChatGPT生成的人工智能报告;由独立审查员评估的人类报告.
- 混合主题分析和使用曼-惠特尼U和费舍尔精确测试的定量比较.
主要成果:
- 人类评论提供了更详细的评论解释,原创性和适用性.
- 人工智能审查涵盖了更多的部分,但专注于结构和例行方面的方面,在格式上略有优势.
- 与集群AI评论相比,人类评论表现出更大的主题多样性和相互联系.
结论:
- 人工智能可以通过识别基本错误来帮助同行审查,但缺乏批判性判断和上下文理解.
- 人类专业知识对于全面和有意义的科学同行评审至关重要.
- 开发机密的,专门用于审查的人工智能工具是必要的,以便在未来融入学术出版.
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