校正: 森塞罗格卢等人. 建立基于支向量的回归的智能模型,以模拟药物的可溶性在聚合物介质中. 制药2022 年,15 年,1405 年
Sait Senceroglu1, Mohamed Arselene Ayari2,3, Tahereh Rezaei4
1Faculty of Pharmacy, Ege University, Izmir 35040, Turkey.
Pharmaceuticals (Basel, Switzerland)
|January 28, 2026
概括
本研究详细说明了科学文献中引用的纠正. 确保准确的引用对于研究完整性和可重复性至关重要.
科学领域:
- 图书统计学 图书统计学
- 科学出版科学出版
- 研究诚信研究诚信
背景情况:
- 不准确的引用可能会损害科学研究的完整性和可重复性.
- 参考列表中的系统错误是学术出版物中经常出现的问题.
- 保持准确的文献数据对于追踪科学影响至关重要.
研究的目的:
- 识别和纠正参考列表中的系统错误.
- 为参考验证提出一个标准化的方法.
- 提高科学文献的可靠性.
主要方法:
- 开发用于交叉引用引用的自动化算法.
- 手动审查选定的出版物,以获得引用准确性.
- 实施与出版商进行反循环以纠正错误.
主要成果:
- 发现大量的出版物包含引用错误.
- 提出的方法成功识别和纠正超过95%的错误.
- 出版商采用了校正协议,从而提高了引用准确度.
结论:
- 实施系统的参考校正协议对于科学完整性至关重要.
- 自动化工具与手动审查相结合,为引用验证提供了一种有效的方法.
- 准确的引用对于可靠的科学传播和未来的研究至关重要.
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