BASE – BAsicranial Sex Estimation: An R package for sexing adult western European individuals from the cranial base morphometry in bioarchaeology and forensic anthropology

Sexing an adult human skeleton from its fragmented remains is a tremendous challenge in both archaeological and forensic contexts. Although reliable sex estimation methods using the os coxae do exist, as well as the possibility of performing a secondary sexual diagnosis within a funerary assemblage, it is essential in the case of fragmented individuals to set up an alternative sex estimation method based on a skeletal element that is both sexually dimorphic and has a high taphonomic survival rate. This study investigated the sexual dimorphism of the cranial base (occipital and temporal bones), through an exclusively metric approach, in 537 identified western European adults. Using logistic regressions, thirteen predictive models were built up, which yielded up to 86.8% accuracy after cross-validation and with a decision threshold of 0.70. BASE is an R package with a graphic user interface that can be used to apply these predictive models to a target adult individual (https://archive.softwareheritage.org/browse/directory/5e3e3753e1f9c360b0ddbebaa2d2b42e5d7686d9). This paper provides measurement definitions, practical details and user recommendations. BASE is a new sex estimation tool which is free of charge, fast and easy to use, and allows anthropologists to collect biological data from larger numbers of individuals, even when their skeletons are highly fragmented and damaged. This new method can certainly contribute to a better understanding of past populations and will be of considerable value to forensic investigations in today’s context of steadily rising numbers of missing persons. BOUCHERIE A. , POLET C. , MARTINE V., LEFÈVRE P., SANTOS F., 2025. BASE – BAsicranial Sex Estimation: An R package for sexing adult western European individuals from the cranial base morphometry in bioarchaeology and forensic anthropology. , (2) :

RBINS Collection(s), PDF available, Open Access, Impact Factor, Peer Review, International Redaction Board

sex estimation, cranial base, logistic regression, R language, machine learning