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• W4387261872 abstract "Sex estimation is one of the crucial trends in cases of findings of unknown skeletal remains in forensics and bioarchaeology. The changing nature of sexual dimorphism (population specificity, secular trend, other external and internal factors influence) brings challenges to developing new methods; and there are new aims to be independent of these changes such, as the method by Musilová et al. (2016). These methods need to be evaluated on different datasets to determine if they are truly reliable among populations from different places and times, in the case of bioarchaeology. This study assessed the application of the aforementioned method on non-European contemporary and ancient populations to identify the reliability of the method on this separate dataset. The study sample consisted of 96 CT scans of skulls from contemporary Egyptians and 54 3D models of skulls from the Egyptian Old Kingdom Period (2,700 to 2,180 BC). The classifier method, previously tested on both Czech and French populations, yielded high accuracies (over 90%) for sex estimation. For the contemporary Egyptian skull sample, the classifier was able to determine males versus females with an 89.59% accuracy rate and an AUC value (area under the curve – a measure of the combined specificity and sensitivity of the test) of 0.99; this proves that the classifier is reliable even with a lower degree of accuracy. Conversely, the Old Kingdom Period sample yielded a lower level of accuracy at around 70% (61.11%, precisely), although with an AUC value of 0.92, the result is not considered reliable." @default.
• W4387261872 created "2023-10-03" @default.
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• W4387261872 date "2023-11-01" @default.
• W4387261872 modified "2023-10-12" @default.
• W4387261872 title "How reliable is the application of the sex classifier based on exocranial surface (Musilová et al., 2016) for geographically and temporally distant skull series" @default.
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• W4387261872 doi "https://doi.org/10.1016/j.forsciint.2023.111850" @default.
• W4387261872 hasPublicationYear "2023" @default.
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