校正:机器学习模型用于预测坎波医学中的冷热模式:一个多中心前性观察性研究
Ayako Maeda-Minami1,2, Tetsuhiro Yoshino2, Kotoe Katayama3
1Faculty of Pharmaceutical Sciences, Tokyo University of Science, Chiba, Japan.
Frontiers in pharmacology
|February 16, 2026
概括
这项研究纠正了先前发表的一篇文章. 修正涉及研究的数字物体标识符 (DOI). 通过更正的DOI提供更多细节.
科学领域:
- 药理学和毒理学 药理学和毒理学
- 生物医学科学 生物医学科学
背景情况:
- 之前的出版物需要修正.
- 修正涉及文章的数字物体标识符 (DOI).
研究的目的:
- 为研究文章提供准确的数字物体标识符 (DOI).
- 确保科学工作的适当引用和可访问性.
主要方法:
- 对文章的元数据进行了纠正.
- 更新数字物体标识符 (DOI) 的参考.
主要成果:
- 现在已经确定了该文章的正确DOI.
- 确保科学出版物的准确引用.
结论:
- 校正有助于正确引用和检索研究.
- 准确的DOI对于科学文献的完整性至关重要.
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