Prioritizing a high posterior probability threshold leading to low error rate over high classification accuracy: the validity of MorphoPASSE software for cranial morphological sex estimation in a contemporary population.

An increasing number of software tools can be used in forensic anthropology to estimate a biological profile, but further studies in other populations are required for more robust validation. The present study aimed to evaluate the validity of MorphoPASSE software for sex estimation from sexually dimorphic cranial traits recorded on 3D CT models (n = 180) from three populations samples (Czech, French, and Egyptian). Two independent observers performed scoring of 4 cranial traits (2 of them bilateral) in each population sample of 30 males and 30 females. The accuracy of sex estimation using traditional posterior probability threshold (pp = 0.5) ranged from 85.6% to 88.3% and overall classification error from 14.4% to 11.7% for both observers, and corresponds to the previously published values of the method. The MorphoPASSE method is also affected by the subjectivity of the observers, as both observers show agreement in sex assignment in 83.9% of cases, regardless of the accuracy of the estimates. Applying a higher posterior probability threshold (pp 0.95) provided classification accuracy of 97.9% and 93.3% of individuals (for observer A and B respectively), minimizing the risk of error to 2.1% and 6.7%, respectively. However, sex estimation can only be applied to 54% and 66% of individuals, respectively. Our results demonstrate the validity of the MorphoPASSE software for cranial sex estimation outside the reference population. However, the achieved classification success is accompanied by a high risk of errors, the reduction of which is only possible by increasing the posterior probability threshold.

Classification performance of the Sella-Tunis et al. (2017) sex estimation method in Czech population: different posterior probability threshold approaches.

In this study we tested classification performance of a sex estimation method from the mandible originally developed by Sella-Tunis et al. (2017) on a heterogeneous Israeli population. Mandibular linear dimensions were measured on 60 CT scans derived from the Czech living population. Classification performance of Israeli discriminant functions (DFs-IL) was analyzed in comparison with calculated Czech discriminant functions (DFs-CZ) while different posterior probability thresholds (currently discussed in the forensic literature) were employed. Our results comprehensively illustrate sensitivity of different discriminant functions to population differences in body size and degree of sexual dimorphism. We demonstrate that the error rate may be biased when presented per posterior probability threshold. DF-IL 1 showed least sensitivity to population origin and fulfilled criteria of sufficient classification performance when applied on the Czech sample with a minimum posterior probability threshold of 0.88 reaching overall accuracy ≥ 95%, zero sex bias, and 80% of classified individuals. The last parameter was higher in DF-CZ 1 which was the main difference between those two DFs suggesting relatively low dependance on population origin. As the use of population-specific methods is often prevented by complicated assessment of population origin, DF-IL 1 is a candidate for a sufficiently robust method that could be reliably applied outside the reference sample, and thus, its classification performance deserves further testing on more population samples.

Automated age-at-death estimation from 3D surface scans of the facies auricularis of the pelvic bone.

This work presents an automated data-mining model for age-at-death estimation based on 3D scans of the auricular surface of the pelvic bone. The study is based on a multi-population sample of 688 individuals (males and females) originating from one Asian and five European identified osteological collections. Our method requires no expert knowledge and achieves similar accuracy compared to traditional subjective methods. Apart from data acquisition, the whole procedure of pre-processing, feature extraction and age estimation is fully automated and implemented as a computer program. This program is a part of a freely available web-based software tool called CoxAGE3D. This software tool is available at https://coxage3d.fit.cvut.cz/ Our age-at-death estimation method is suitable for use on individuals with known/unknown population affinity and provides moderate correlation between the estimated age and actual age (Pearson's correlation coefficient is 0.56), and a mean absolute error of 12.4 years.