使用人工智能来改善同行评审和科学期刊的研究完整性
Howard Bauchner1, Frederick Rivara2
1Boston University Chobanian & Avedisian School of Medicine, Visiting Scholar, National University of Singapore.
Health affairs scholar
|February 25, 2026
概括
同行评审在效率和有效性方面面临挑战. 人工智能 (AI) 在日益增长的出版量和公众对科学怀疑的背景下,为提高研究完整性提供了一个潜在的解决方案.
科学领域:
- 生物医学科学 生物医学科学
- 科学出版科学出版
- 研究诚信研究诚信
背景情况:
- 传统的同行评审越来越低效,偏见和无效.
- 保持研究完整性至关重要,尤其是在公众对科学信心下降的情况下.
- 每年超过300万份生物医学手稿的庞大数量压倒了手册审查过程.
研究的目的:
- 突出目前同行评审系统的局限性.
- 强调需要新的方法来确保科学完整性.
- 引入人工智能 (AI) 作为增强编辑和同行评审的工具.
主要方法:
- 分析科学出版和同行评审的现状.
- 确定在维护研究完整性方面面临的挑战.
- 探索人工智能作为对手稿评价的补充工具.
主要成果:
- 目前的同行评审方法不足以保证快速增长的科学文献的完整性.
- 人类编辑和同行评审本身无法应对生物医学出版物的规模.
- 人工智能提供了一个可行的选择,可以协助编辑和同行评审过程.
结论:
- 为了维护研究完整性,新的战略是必不可少的.
- 人工智能可以在提高同行评审的效率和有效性方面发挥重要作用.
- 整合人工智能是管理越来越多的科学出版物的必要,并保持公众对科学的信任.
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