Suppr超能文献

从椎骨推断性别存在种群特异性。

Population specificity of sex estimation from vertebrae.

机构信息

Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Viničná 7, 12843 Praha 2, Prague, Czech Republic.

Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Viničná 7, 12843 Praha 2, Prague, Czech Republic.

出版信息

Forensic Sci Int. 2018 Oct;291:279.e1-279.e12. doi: 10.1016/j.forsciint.2018.08.015. Epub 2018 Aug 25.

Abstract

Vertebral measurements have been shown to provide accurate classification of sex. However, the use of vertebral discriminant functions (DFs) in forensic anthropology and bioarchaeology is limited due to the unknown degree of their population specificity. Additionally, the performance of vertebral DFs has not yet been assessed at higher posterior probability thresholds. In this study, we tested the performance of previously published DFs for sex classification from Th12 and L1 vertebrae within a range of 0.5-0.95 posterior probabilities in a model of geographically distant population based on an autopsy Central European (CE) sample (Czech Republic; n=72) from the 1930s. Further, we derived new pooled DFs from a sample representing ecogeographically diverse populations, new DFs derived from the autopsy CE sample, and new Medieval CE DFs derived from the Pohansko sample (n=129) and evaluated their performance at our testing autopsy CE sample. Most vertebral measurements showed population specificity in sex assessment. However, we identified two Th12 measurements (anteroposterior body diameter and mediolateral body diameter) usable for sex estimation across populations. We showed that the accuracy of vertebral DFs can be increased to 95% of correctly classified individuals in up to 64% of the studied sample by setting a higher posterior probability threshold. Finally, we showed that even the DFs derived from relatively small subsamples (30% of the population size) can provide accurate sex classification. This finding highlights the applicability of the hybrid approach in sex classification from vertebrae. To facilitate sex classification from vertebrae, we provide a software tool for sex classification from any vertebral measurement and reference samples tested in this study including the previously published DFs.

摘要

椎体测量已被证明可用于准确的性别分类。然而,由于未知的人群特异性程度,椎体判别函数(DFs)在法医人类学和生物考古学中的应用受到限制。此外,椎体 DFs 的性能尚未在更高的后验概率阈值下进行评估。在这项研究中,我们在基于地理上遥远的人群的模型中,在 0.5-0.95 后验概率范围内,测试了之前发表的用于 Th12 和 L1 椎体性别分类的 DFs 的性能,该模型基于 20 世纪 30 年代来自中欧(CE)尸检样本(捷克共和国;n=72)的尸体。此外,我们从代表生态地理多样化人群的样本中推导出新的混合 DFs,从尸检 CE 样本中推导出新的 DFs,以及从 Pohansko 样本(n=129)中推导出新的中世纪 CE DFs,并在我们的尸检 CE 样本中评估它们的性能。大多数椎体测量在性别评估中表现出人群特异性。然而,我们确定了两个可用于跨人群进行性别估计的 Th12 测量值(前后体直径和左右体直径)。我们表明,通过设置更高的后验概率阈值,椎体 DFs 的准确性可以提高到可正确分类个体的 95%,在研究样本的 64%内。最后,我们表明,即使是从相对较小的子样本(人群的 30%)中推导出来的 DFs 也可以提供准确的性别分类。这一发现突出了混合方法在椎体性别分类中的适用性。为了方便从椎体进行性别分类,我们提供了一个用于从任何椎体测量值进行性别分类的软件工具,并提供了在本研究中测试的参考样本,包括之前发表的 DFs。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验