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塞拉-图尼斯等人的分类表现. (2017) 捷克人口的性别估计方法:不同的后后概率值方法
Rebeka Rmoutilová1,2, Kateřina Piskačová3, Anežka Pilmann Kotěrová3
1Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Viničná 7, 128 43, Prague, Czech Republic. vejnaror@natur.cuni.cz.
International journal of legal medicine
|May 7, 2024
概括
这项研究在捷克人口中测试了一种使用下巴测量的性别估计方法. 以色列的区分函数 (DF-IL 1) 显示出强大的性能,这表明其潜在的应用范围超出了其原始参考样本.
科学领域:
- 法医人类学 法医人类学
- 生物考古学的生物考古学
- 人类骨科人类骨科
背景情况:
- 准确的性别估计在法医人类学中至关重要.
- 部形态测量分析提供了一个可行的方法来确定性别.
- 特定种群的变化可能会影响现有方法的准确性.
研究的目的:
- 评估分类表现的性别估计方法从下巴在一个异质的以色列人口的分类表现.
- 为了比较以色列歧视函数 (DFs-IL) 与捷克歧视函数 (DFs-CZ) 的性能.
- 评估不同后置概率值对分类准确性的影响.
主要方法:
- mandibular 线性维度是从捷克生活人口的 60 个 CT 扫描中测量出来的.
- 用从以色列和捷克样本中获得的区分函数分析了分类性能.
- 用各种后置概率值来评估分类准确性和偏差.
主要成果:
- 当 DF-IL 1 适用于捷克样本时,对人口来源的敏感性最低.
- DF-IL 1实现了≥95%的准确性,零性别偏差,80%的个人在0.88后置概率值下被分类.
- DF-CZ 1显示了最后一个参数的更高率,表明对人口来源的依赖相对较低.
结论:
- DF-IL 1 显示出足够的稳定性,可用于其参考样本之外的潜在应用.
- 这项研究突出了歧视性功能对人群体积和性二态的特定差异的敏感性.
- 建议在更多的人口样本上对DF-IL 1进行进一步测试,以确认其可靠性.
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