在生成性AI时代,冗余出版物的急剧增加
Danny Maupin1, Tulsi Suchak1, Adrian Barnett2
1School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, UK.
BMC medicine
|December 9, 2025
概括
由于生成AI (GenAI),冗余出版物激增,人工智能生成的手稿避开了当前的抄袭检查. 这表明编辑完整性的系统性失败,需要更新的指导方针来保护科学记录.
科学领域:
- 科学完整性 科学完整性
- 图书统计学 图书统计学
- 卫生研究伦理 卫生研究伦理
背景情况:
- 冗余的出版物扭曲了科学记录,浪费了资源.
- 越来越多地使用大型开放科学数据,如NHANES,引发了人们对人工智能促进的冗余手稿的担忧.
- 生成型人工智能 (GenAI) 可能正在实现创建公式式,冗余的出版物.
研究的目的:
- 从一个单一的大型健康数据集 (NHANES) 中量化冗余出版物.
- 为了调查GenAI是否可以生产能够逃避标准完整性检查的合成手稿.
- 在GenAI时代评估当前窃检测的有效性.
主要方法:
- 使用NHANES数据 (2021-2025) 系统搜索冗余出版物.
- 冗余的定义:相同的暴露,结果和国家人口.
- 促使GenAI创建旨在逃避检测的合成手稿;用抄袭软件进行测试.
主要成果:
- 在156个暴露-结果配对中,确定了411个冗余出版物.
- 例如:NHANES关于氧化平衡得分和慢性病的数据在一年内发表了6次.
- 基因AI生成的手稿显示相似度得分较低 (14-26%),避开了典型的抄袭值.
结论:
- 冗余出版物的17倍增长 (2022-2024) 标志着编辑检查的系统性失败.
- 冗余的论文扭曲了研究 (元分析,科学计量) 并浪费了同行评审资源.
- 目前的抄袭和冗余检查对GenAI来说不足;出版商需要加强合作和指导方针.
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