(hu)MANid程序在不同下颌骨样本上的测试

P. Lynch, Luis Lorenzo Cabo-Pérez
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引用次数: 2

摘要

MANid程序是一个免费的基于网络的软件,使用下颌度量和形态变量来估计性别和祖先。该数据库由来自15个种群(现代、历史和史前)的1745个个体组成。下颌计的使用有两个限制。这是一种昂贵的设备,并非所有实验室都有,而且许多用户没有使用下颌计的经验,因此误差可能很高。为了解决这个问题,三维表面扫描(3D扫描)为数据收集提供了另一种方法。在这里,作者评估了(hu)MANid程序在不同样本上的准确性,比较了3D扫描和物理测量的准确性,并评估下颌计测量是否提高了分类率。从3D扫描(Ntotal = 555)和骨骼(Ntotal = 41)中收集了6个度量和形态学变量。另外还从骨头上收集了三个下颌测量仪的测量值。由于报告的分类正确率较高,使用逐步选择时没有显著差异,因此采用混合判别分析和非逐步选择。与数字测量相匹配的参考组的测试样本对祖先和性别/祖先组合的正确分类高于平均机会。除了使用数字测量的女性之外,所有比较的汇总性别分类的正确率都高于正确率。尽管样本量小,但物理测量比数字测量具有更高的正确分类率。包括下颌测量并没有显著增加物理测量的分类率。结果表明,hu(MAN)id比chance更好,但由于物理测量缺乏多样性,建议进行额外的测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Test of the (hu)MANid Program on a Diverse Sample of Mandibles
The (hu)MANid program is a free, web-based software using mandibular metric and morphoscopic variables to estimate sex and ancestry. The database consists of 1,745 individuals from 15 populations (modern, historic, and prehistoric). The required use of a mandibulometer presents two limitations. It is an expensive piece of equipment not available in all labs, and many users do not have experience using a mandibulometer, so error can be high. To address this, three-dimensional surface scans (3D scans) provide an alternative method for data collection. Here, the authors assess the accuracy of the (hu)MANid program on a diverse sample, compare accuracy from 3D scans and physical measurements, and evaluate whether mandibulometer measurements increase classification rates. Six metric and morphoscopic variables were collected from 3D scans (Ntotal = 555) and from bone (Ntotal = 41). Three additional mandibulometer measurements were collected from bone. Mixture discriminant analysis and non-stepwise options were applied due to reported higher correct classification and no significant difference when using stepwise options. Test samples with matching reference groups from the digital measurements had higher than chance average correct classifications for ancestry and sex/ancestry combined. Pooled sexes had correct classifications higher than chance for all comparisons except females using digital measurements. Physical measurements had a higher correct classification rate than digital measurements despite the small sample size. Including mandibulometer measurements did not significantly increase classification rates for physical measurements. Results indicate that hu(MAN)id is better than chance but suggest additional testing due to a lack of diversity in the physical measurements.
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