Revisiting metric sex estimation of burnt human remains via supervised learning using a reference collection of modern identified cremated individuals (Knoxville, USA).
Objectives: This study aims to increase the rate of correctly sexed calcined individuals from archaeological and forensic contexts. This is achieved by evaluating sexual dimorphism of commonly used and new skeletal elements via uni‐ and multi‐variate metric trait analyses. Materials and methods: Twe...
| Publicado en: | American Journal of Physical Anthropology Vol. 175; no. 4; pp. 777 - 794 |
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| Autores principales: | , , , , , , , , , , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
Aug2021
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=151432696&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 151432696 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00029483 APX jtl: American Journal of Physical Anthropology issn: 00029483 maglogo: Y pubinfo: dt: Aug2021 vid: 175 iid: 4 pid: 480 pub: Wiley-Blackwell artinfo: ui: 151432696 10.1002/ajpa.24270 ppf: 777 ppct: 17 formats: tig: atl: Revisiting metric sex estimation of burnt human remains via supervised learning using a reference collection of modern identified cremated individuals (Knoxville, USA). aug: au: Hlad, Marta Veselka, Barbara Steadman, Dawnie Wolfe Herregods, Baptiste Elskens, Marc Annaert, Rica Boudin, Mathieu Capuzzo, Giacomo Dalle, Sarah De Mulder, Guy Sabaux, Charlotte Salesse, Kevin Sengeløv, Amanda Stamataki, Elisavet Vercauteren, Martine Warmenbol, Eugène Tys, Dries Snoeck, Christophe affil: Maritime Cultures Research Institute, Department of History, Archaeology, Arts, Philosophy and Ethics, Vrije Universiteit Brussel, Brussels, Belgium Research Unit Anthropology and Human Genetics, Faculty of Science, Université Libre de Bruxelles, Brussels, Belgium Department of Anthropology, University of Tennessee, Knoxville Tennessee,, USA Independent researcher, Brussels, Belgium Research Unit Analytical, Environmental and Geo‐Chemistry, Department of Chemistry, Vrije Universiteit Brussel, AMGC‐WE‐VUB, Brussels, Belgium Flemish Heritage Agency, Brussels, Belgium Radiocarbon Dating Laboratory, Royal Institute for Cultural Heritage, Brussels, Belgium Department of Archaeology, Ghent University, Ghent, Belgium UMR 5199: "PACEA ‐ De la Préhistoire à l'Actuel: Culture, Environnement et Anthropologie", University of Bordeaux, Pessac cedex, France Center de Recherches en Archéologie et Patrimoine, Department of History, Arts, and Archaeology, Université Libre de Bruxelles, Brussels, Belgium G‐Time Laboratory, Université Libre de Bruxelles, Brussels, Belgium su: Sex determination of human remains Supervised learning Sexual dimorphism Neural circuitry Random forest algorithms sug: subj: Sex determination of human remains Supervised learning Sexual dimorphism Neural circuitry Random forest algorithms keyword: calcined human bones metric traits multivariate analysis sexual dimorphism calcined human bones metric traits multivariate analysis sexual dimorphism ab: Objectives: This study aims to increase the rate of correctly sexed calcined individuals from archaeological and forensic contexts. This is achieved by evaluating sexual dimorphism of commonly used and new skeletal elements via uni‐ and multi‐variate metric trait analyses. Materials and methods: Twenty‐two skeletal traits were evaluated in 86 individuals from the William M. Bass donated cremated collection of known sex and age‐at‐death. Four different predictive models, logistic regression, random forest, neural network, and calculation of population specific cut‐off points, were used to determine the classification accuracy (CA) of each feature and several combinations thereof. Results: An overall CA of ≥ 80% was obtained for 12 out of 22 features (humerus trochlea max., and lunate length, humerus head vertical diameter, humerus head transverse diameter, radius head max., femur head vertical diameter, patella width, patella thickness, and talus trochlea length) using univariate analysis. Multivariate analysis showed an increase of CA (≥ 95%) for certain combinations and models (e.g., humerus trochlea max. and patella thickness). Our study shows metric sexual dimorphism to be well preserved in calcined human remains, despite the changes that occur during burning. Conclusions: Our study demonstrated the potential of machine learning approaches, such as neural networks, for multivariate analyses. Using these statistical methods improves the rate of correct sex estimations in calcined human remains and can be applied to highly fragmented unburnt individuals from both archaeological and forensic contexts. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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