人工智能的使用和同行评审的未来
Howard Bauchner1, Frederick P Rivara2
1Boston University Chobanian & Avedisian School of Medicine, Visiting Scholars Program, National University of Singapore, 02118, Singapore.
Health affairs scholar
|May 17, 2024
概括
高质量的科学同行评审面临着挑战. 人工智能 (AI),特别是大语言模型,提供了一个有前途的解决方案,以协助手稿分类和改进审查过程.
科学领域:
- 科学出版科学出版
- 人工智能的人工智能
- 医学研究 医学研究
背景情况:
- 越来越多的科学手稿给传统的同行评审带来了重大挑战.
- 缺乏合格的同行评审者会影响评审过程的有效性,公平性和效率.
- 现有的同行评审系统很难应对现代科学出版的要求.
研究的目的:
- 探索人工智能 (AI) 在解决科学稿件同行评审方面的挑战方面的潜力.
- 建议使用大语言模型 (LLM) 作为一种工具,以协助手稿的初始选和分类.
- 通过人工智能驱动的支持,提高同行评审过程的效率和有效性.
主要方法:
- 审查当前的挑战在科学同行评审.
- 探索大语言模型 (LLM) 作为人工智能 (AI) 的一种形式.
- 关于将人工智能整合到稿件提交和分类工作流程中的概念建议.
主要成果:
- 确定了手稿量,审稿人可用性和流程效率方面的重大挑战.
- 强调了LLM在处理和分析大量文本数据方面的能力.
- 展示了人工智能有助于识别适合审查的手稿的潜力.
结论:
- 人工智能,特别是LLM,为增强科学同行评审提供了一个可行的解决方案.
- 人工智能辅助的分类可以提高手稿选择的效率和公平性.
- 整合人工智能对于未来的高质量科学出版和医学研究至关重要.
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