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A method of sexing the human os coxae based on logistic regressions and Bruzek's nonmetric traits
F. Santos, P. Guyomarc'h, R. Rmoutilova, J. Bruzek,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
GAČR 14-22823S
Grantová Agentura České Republiky - International
GAUK 1088217
Grantová Agentura, Univerzita Karlova - International
PubMed
31093965
DOI
10.1002/ajpa.23855
Knihovny.cz E-zdroje
- MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- logistické modely * MeSH
- mladý dospělý MeSH
- pánevní kosti anatomie a histologie MeSH
- počítačová rentgenová tomografie MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- soudní antropologie metody MeSH
- určení pohlaví podle kostry metody MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
OBJECTIVES: This study aims at proposing a visual method for sexing the human os coxae based on a statistical approach, using a scoring system of traits described by Bruzek (2002). This method is evaluated on a meta-population sample, where the data were acquired by direct observation of dry bones as well as computed tomography (CT) scans. A comparison with the original Bruzek's (2002) method is performed. MATERIALS AND METHODS: Five hundred and ninety two ossa coxae of modern humans are included in the reference dataset. Two other samples, composed respectively of 518 ossa coxae and 99 CT-scan images, are both used for validation purposes. The individuals come from five European or North American population samples. Eleven trichotomic traits (expressing female, male, or intermediate forms) were observed on each os coxae. The new approach employs statistical processing based on logistic regressions. An R package freely available online, PELVIS, implements both methods. RESULTS: Both methods provide highly reliable sex estimates. The new statistical method has a slightly better accuracy rate (99.2%) than the former method (98.2%) but has also a higher rate of indeterminate individuals (12.9% vs. 3% for complete bones). CONCLUSION: The efficiency of both methods is compared. Low error rates were preferred over high ability of reaching the classification threshold. The impact of lateralization and the asymmetry of observed traits are discussed. Finally, it is shown that this visual method of sex estimation is reliable and easy to use through the graphical user interface of the R package.
Université Aix Marseille CNRS EFS UMR 7268 ADES Marseille France
Université de Bordeaux CNRS MCC UMR 5199 PACEA Pessac France
Citace poskytuje Crossref.org
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- $a OBJECTIVES: This study aims at proposing a visual method for sexing the human os coxae based on a statistical approach, using a scoring system of traits described by Bruzek (2002). This method is evaluated on a meta-population sample, where the data were acquired by direct observation of dry bones as well as computed tomography (CT) scans. A comparison with the original Bruzek's (2002) method is performed. MATERIALS AND METHODS: Five hundred and ninety two ossa coxae of modern humans are included in the reference dataset. Two other samples, composed respectively of 518 ossa coxae and 99 CT-scan images, are both used for validation purposes. The individuals come from five European or North American population samples. Eleven trichotomic traits (expressing female, male, or intermediate forms) were observed on each os coxae. The new approach employs statistical processing based on logistic regressions. An R package freely available online, PELVIS, implements both methods. RESULTS: Both methods provide highly reliable sex estimates. The new statistical method has a slightly better accuracy rate (99.2%) than the former method (98.2%) but has also a higher rate of indeterminate individuals (12.9% vs. 3% for complete bones). CONCLUSION: The efficiency of both methods is compared. Low error rates were preferred over high ability of reaching the classification threshold. The impact of lateralization and the asymmetry of observed traits are discussed. Finally, it is shown that this visual method of sex estimation is reliable and easy to use through the graphical user interface of the R package.
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