揭示了来自造纸厂的科学文章,并进行了来源分析
João Phillipe Cardenuto1, Daniel Moreira2, Anderson Rocha1
1Artificial Intelligence Lab. Recod.ai, Institute of Computing, Universidade Estadual de Campinas, Campinas, São Paulo, Brazil.
PloS one
|October 30, 2024
概括
检测伪造的科学出版物是一个挑战. 这项研究引入了一种新的来源分析方法,可以追踪数字,自动分组并识别来自同一纸厂的产品,从而提高科学完整性.
科学领域:
- 科学完整性 科学完整性
- 图书统计学 图书统计学
- 图像分析 图像分析
背景情况:
- 造纸厂产生虚假的出版物,挑战科学诚信.
- 目前用于识别欺诈性文章的方法通常是手动和低效的.
- 假出版物经常使用重复或操纵的数字进行传播.
研究的目的:
- 开发一种自动化的方法来识别系统地制作的欺诈性出版物.
- 根据图形分析,将来自同一纸厂的手稿组合在一起.
- 通过检测造纸厂活动,提供一种提高科学诚信的工具.
主要方法:
- 开发了一个来源分析方法来追踪和分组可疑的数字和文件.
- 实施图形分析,以识别手稿中重复和操纵的区域.
- 构建了一个来源图,以链接和组织系统生产的证据.
主要成果:
- 成功地将纸厂系统生产的产品分组到不同大小的数据集中.
- 识别了重复使用和操纵的数字作为欺诈性手稿制作的关键指标.
- 证明了该方法的有效性,即使面对有意分散数据.
结论:
- 提出的来源分析技术为检测欺诈性手稿提供了一个有希望的自动化解决方案.
- 这种方法可以通过分析数字的重复使用和操纵,有效地识别纸厂生产的产品.
- 该工具通过提供系统欺诈性出版实践的证据来支持科学诚信.
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