大型语言模型在同行评审过程中的作用:医学期刊审稿人和编辑的机遇和挑战。

IF 9.3 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Jisoo Lee, Jieun Lee, Jeong-Ju Yoo
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引用次数: 0

摘要

同行评议过程确保了科学研究的完整性。这在医学领域尤其重要,因为研究结果直接影响到病人的护理。然而,出版物的快速增长使审稿人感到紧张,导致延迟和潜在的质量下降。生成式人工智能,尤其是像ChatGPT这样的大型语言模型(llm),可以帮助研究人员进行高效、高质量的评论。这篇综述探讨了法学硕士与同行评审的整合,强调了他们在语言任务中的优势和评估科学有效性的挑战,特别是在临床医学中。集成的关键点包括初始筛选、审稿人匹配、反馈支持和语言审查。然而,为这些目的实施法学硕士将需要解决偏见、隐私问题和数据机密性问题。我们建议在明确的指导方针下使用法学硕士作为补充工具,以支持而不是取代维护严格的同行评审标准的人类专业知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors.

The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist researchers with efficient, high-quality reviews. This review explores the integration of LLMs into peer review, highlighting their strengths in linguistic tasks and challenges in assessing scientific validity, particularly in clinical medicine. Key points for integration include initial screening, reviewer matching, feedback support, and language review. However, implementing LLMs for these purposes will necessitate addressing biases, privacy concerns, and data confidentiality. We recommend using LLMs as complementary tools under clear guidelines to support, not replace, human expertise in maintaining rigorous peer review standards.

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来源期刊
CiteScore
9.60
自引率
9.10%
发文量
32
审稿时长
5 weeks
期刊介绍: Journal of Educational Evaluation for Health Professions aims to provide readers the state-of-the art practical information on the educational evaluation for health professions so that to increase the quality of undergraduate, graduate, and continuing education. It is specialized in educational evaluation including adoption of measurement theory to medical health education, promotion of high stakes examination such as national licensing examinations, improvement of nationwide or international programs of education, computer-based testing, computerized adaptive testing, and medical health regulatory bodies. Its field comprises a variety of professions that address public medical health as following but not limited to: Care workers Dental hygienists Dental technicians Dentists Dietitians Emergency medical technicians Health educators Medical record technicians Medical technologists Midwives Nurses Nursing aides Occupational therapists Opticians Oriental medical doctors Oriental medicine dispensers Oriental pharmacists Pharmacists Physical therapists Physicians Prosthetists and Orthotists Radiological technologists Rehabilitation counselor Sanitary technicians Speech-language therapists.
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