According to the provided measurements, the chosen model predicts the following
Model Summary
Authors
Francisco Curate, João Coelho, David Gonçalves, Catarina Coelho, Maria Teresa Ferreira, David Navega, Eugénia Cunha.
Laboratory of Forensic Anthropology, Life Sciences Department, University of CoimbraAbstract
The assessment of sex is crucial to the establishment of a biological profile of an unidentified skeletal individual. The best methods currently available for the sexual diagnosis of human skeletal remains generally rely on the presence of well-preserved pelvic bones, which is not always the case. Postcranial elements, including the femur, have been used to accurately estimate sex in skeletal remains from forensic and bioarcheological settings. In this study, we present an approach to estimate sex using two measurements (femoral neck width [FNW] and femoral neck axis length [FNAL]) of the proximal femur. FNW and FNAL were obtained in a training sample (114 females and 138 males) from the Luís Lopes Collection (National History Museum of Lisbon). Logistic regression and the C4.5 algorithm were used to develop models to predict sex in unknown individuals. Proposed cross-validated models correctly predicted sex in 82.5% to 85.7% of the cases. The models were also evaluated in a test sample (96 females and 96 males) from the Coimbra Identified Skeletal Collection (University of Coimbra), resulting in a sex allocation accuracy of 80.1% to 86.2%. This study supports the relative value of the proximal femur to estimate sex in skeletal remains, especially when other exceedingly dimorphic skeletal elements are not accessible for analysis.
Keywords: forensic anthropology, population data, forensic science, human identification, biological profile