为了减少科幻小说的科学摩擦,更多的科学摩擦
Jennifer A Byrne1,2, Stefan Stender3,4
1NSW Health Statewide Biobank, NSW Health Pathology, Camperdown, Australia.
PLoS biology
|May 9, 2025
概括
人工智能准备好的健康数据集可以导致无数具有很少科学价值的研究论文. 一项在PLOS生物学上的研究显示,最近大量的出版物分析了国家健康和营养检查调查 (NHANES) 数据集.
科学领域:
- 医疗信息学 医疗信息学
- 图书统计学 图书统计学
- 研究中的人工智能.
背景情况:
- 越来越多的大型,AI-ready健康数据集的可用性为科学研究带来了机遇和挑战.
- 国家健康和营养检查调查 (NHANES) 是一个广泛使用的公共卫生数据集.
研究的目的:
- 调查从AI准备的健康数据集生成研究文章的趋势.
- 分析最近NHANES专题出版物激增的科学价值和影响.
主要方法:
- 研究出版物的图书统计分析.
- 在科学文献中使用数据集的趋势分析.
- 从NHANES数据对研究成果的定性评估.
主要成果:
- 观察到分析NHANES数据集的研究文章数量显著且快速增加.
- 这些文章的很大一部分可能提供有限的新科学贡献.
- 易于访问AI准备的数据集可以激励研究成果的数量而不是质量.
结论:
- 来自像NHANES这样的AI准备数据集的研究论文的激增,需要进行批判性评估.
- 需要制定战略,以确保数据驱动的研究保持高科学标准和价值.
- 需要进一步的研究,以了解人工智能驱动的出版趋势对科学进步的长期影响.
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