纠正:利用可解释的机器学习在重症监护室早期预测心脏骤停:回顾性研究
Yun Kwan Kim1,2, Won-Doo Seo1, Sun Jung Lee1
1Technology Development, Seers Technology Co. Ltd., Pyeongtaek-si, Gyeonggi-do, Republic of Korea.
Journal of medical Internet research
|October 28, 2024
概括
这项研究纠正了上一篇文章的数字物体标识符 (DOI). 校正确保研究人员准确引用和检索科学工作.
科学领域:
- 科学出版业的科学出版.
- 学术传播学术交流
背景情况:
- 准确的引用对于科学完整性至关重要.
- 数字物体识别器 (DOI) 对于定位研究文章至关重要.
研究的目的:
- 在发表的文章中纠正错误的DOI.
- 确保研究的正确归因和可访问性.
主要方法:
- 识别错误的DOI. 这是一个错误的DOI.
- 通过出版商记录验证正确的DOI.
- 发出一个纠正通知.
主要成果:
- 错误的DOI已被确定并纠正.
- 修正后的DOI现在与该产品相关联.
- 预计会提高可发现性和引用准确性.
结论:
- 校正DOI是学术出版的重要过程.
- 确保准确的元数据可以提高科学文献的可靠性.
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