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Despite developing prior to the appearance of secondary sexual characteristics of the skeleton, the permanent dentition exhibits sexual dimorphism. Therefore, teeth can serve as a means to estimate sex assigned at birth even in young individuals. This project takes a large global sample of maximum dimensions of the crown as well as measurements of the crown at the cervix to explore sexual dimorphism. Dimorphism is noted in teeth throughout the dental arcade, particularly in the canines. We provide sectioning points as well as the probability of correct classification (ranging from 50.9% to 81.3%) for each measurement to aid the practitioner in sex estimation from the dentition. This research provides a method to estimate sex without arbitrary population specifications. We argue for a global approach that incorporates more population variation to remove the need to estimate "ancestry," (which in actuality is translated to a social race category) and therefore does not force sexual dimorphism-related variation into these mutable and ambiguous categories. Further, this paper demonstrates the utility of the dentition as an additional indicator to aid with the estimation of sex assigned at birth in forensic anthropology. The goal of this research is to better understand the expression of sexual dimorphism across the skeleton in a global context.

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Thanks to technical progress and the availability of virtual data, sex estimation methods as part of a biological profile are undergoing an inevitable evolution. Further reductions in subjectivity, but potentially also in measurement errors, can be brought by approaches that automate the extraction of variables. Such automatization also significantly accelerates and facilitates the specialist's work. The aim of this study is (1) to apply a previously proposed algorithm (Kuchar et al. 2021) to automatically extract 10 variables used for the DSP2 sex estimation method, and (2) to test the robustness of the new automatic approach in a current heterogeneous population. For the first aim, we used a sample of 240 3D scans of pelvic bones from the same individuals, which were measured manually for the DSP database. For the second aim a sample of 108 pelvic bones from the New Mexico Decedent Image Database was used. The results showed high agreement between automatic and manual measurements with rTEM below 5% for all dimensions except two. The accuracy of final sex estimates based on all 10 variables was excellent (error rate 0.3%). However, we observed a higher number of undetermined individuals in the Portuguese sample (25% of males) and the New Mexican sample (36.5% of females). In conclusion, the procedure for automatic dimension extraction was successfully applied both to a different type of data and to a heterogeneous population.

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In this study, we assessed the sexual dimorphism of the contemporary Japanese skull and established sex discriminant function equations based on cranial measurements using three-dimensional (3D) computed tomography (CT) images. The CT images of 263 corpses (142 males, 121 females) that underwent postmortem CT scanning and subsequent forensic autopsy were evaluated. Twenty-one cranial measurements were obtained from 3D CT reconstructed images, which extracted only bone data. We performed descriptive statistics and discriminant function analyses for the measurements. Nineteen measurements were significantly larger in males, suggesting sexual dimorphism of the Japanese skulls. Univariate discriminant function analyses using these measurements showed a sex classification accuracy of 57.8-88.2%, and bizygomatic breadth provided the highest correct prediction rate. Multivariate discriminant function analyses offered the most accurate model using seven variables with an estimation rate of 93.9%. Our results suggest that cranial measurements based on 3D CT images may help in the sex estimation of unidentified bodies in a contemporary Japanese population.

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Sex estimation is a necessary part of forensic and osteological analyses of skeletal human remains in the construction of a biological profile. Several skeletal traits are sexually dimorphic and used for skeletal sex estimation. The human mandible and morphological traits therein have been long used for sex estimation, but the validity of using the mandible in this purpose has become a concern. In this study, we examined the potential of artificial intelligence (AI) and especially deep learning (DL) to provide accurate sex estimations from the mandible. We used 193 modern South African mandibles from the Human Osteological Research Collection (HORC) in the Sefako Makgatho Health Sciences university with known sex to conduct our study. All mandibles were photographed from the same angle and the photographs were analyzed with an open-source DL software. The best-performing DL algorithm estimated the sex of males with 100% accuracy and females with 76.9% accuracy. However, further studies with a higher number of specimens could provide more reliable validity for using AI when building the biological profile from skeletal remains.

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This study aimed to assess the reliability of predictive models for sex estimation based on permanent canine size. A systematic literature review was performed by following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). Six electronic databases were searched as the primary source of information. As a secondary source of information, a manual search was performed to identify additional relevant studies not captured in the initial search. After assessing the methodological quality and risk of bias with the Joanna Briggs Institute Critical Appraisal Tools for Systematic Reviews, the data were subjected to statistical tests for a meta-analysis of diagnostic test accuracy and Higgin's I2 statistic to evaluate the heterogeneity between the eligible studies. The systematic search resulted in 21 studies for qualitative synthesis, and 13 of them were selected for quantitative analysis. The analysis of 25 univariate predictive models showed an estimated sensitivity of 77.2 % and specificity of 67.1 %. Meta-regression analyses were performed for dental arch, the type of diameter and dental region outcomes for these univariate predictive models. Dental arch (p = 0.029) and the dental region of measurement (p = 0.001) were significant modifiers. The analysis of 25 multivariate predictive models showed an estimated sensitivity of 82.6 % and specificity of 70.1 %. There were significant methodological limitations and substantial heterogeneity among the included studies. Based on the results, there is insufficient high-quality scientific evidence to support the safe use of predictive models based on permanent canine measurements as the exclusive method for sex estimation in forensic settings.

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Estimating biological sex is a crucial aspect of forensic anthropology, and is pivotal in forensic investigations. Presently, the most frequently adopted osteological sex estimation methods focus on the anterior pelvis, which is easily susceptible to postmortem damage, revealing a need for additional accurate methods. This study introduces a novel method for estimating adult sex through metric pelvic scar analysis, using a known skeletal sample (169 females; 51 males). Relationships between sex and scar dimensions were subjected to Kendall's tau-B testing, and the strongest associated measurements were further analyzed using binary logistic regression to determine their predictive capacity. The final estimation method was tested on an additional known-sex sample of 43 males and 43 females from the Spitalfields skeletal collection. All associations between biological sex and scar measurements were significant, with the preauricular sulcus and newly defined inferior interosseous cavity presenting the strongest relationships (τb 0.223-0.504). Individual regression models using the approximate volume of each feature predicted sex with over 80% accuracy, but when combined in a single regression model, the accuracy increased to an impressive 97.1%. When then applied to the validation sample, the final estimation model achieved an accuracy of 90.7%. These results highlight the high estimation accuracy achieved by simultaneously utilizing the approximate volume of the sulcus and the inferior cavity. This is not only highly accurate but also utilizes the sturdier posterior pelvis, making it a promising tool for forensic investigations and the wider field of osteology.

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Forensic practitioners need contemporary anthropological data for the identification of human remains. The clavicle possesses a high degree of variability in its anatomical, biomechanical, and morphological features that are sex-dependent albeit population specific. The aim of this study was to develop sex estimation models for Malaysian individuals using post-mortem computed tomographic images of the clavicle. Sample comprised scans of 2.0 mm resolution of 405 individuals (209 male; 196 female) aged between 19 to 88 years. These scans were reconstructed and visualized using Infinitt. Six clavicular measurements (i.e. maximum length, C1; midshaft circumference, C2; midshaft maximum diameter, C3; midshaft minimum diameter, C4; maximum breadth of the sternal end, C5; and maximum breadth of the acromial articular surface, C6) were obtained from these images. Data were analyzed using descriptive statistics and discriminant function analysis. Measurements taken from the images were highly precise (ICC = 0.770-0.999). There is a significant difference between all parameters and sex (p < 0.001), however none for age and ethnic group. A multivariate sex estimation model was developed: Sex = (C1*0.86) + (C2*0.236) + (C3*-0.145) + (C5*- 0.074) - 17.618; with an accuracy rate of 89.1 % and sex bias of -3.2 %. Lower accuracy rates were obtained for single variable models (61.5-83.2 %). The resultant sex discriminant models can be used for estimating sex based on the clavicle in our local forensic practice.

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Determining an individual's sex is crucial in several fields, such as forensic anthropology, archaeology, and medicine. Accurate sex estimation, alongside the estimation of age at death, stature, and ancestry, is of paramount importance for creating a biological profile. This profile helps narrow the potential pool of missing persons and aids identification. Our research focuses on the second cervical vertebra and odontoid process, which is particularly valuable due to their high sexual dimorphism. This brief research is structured as follows: we provide an overview of morphometric analysis of the second cervical vertebra for accurate sex estimation in forensic anthropology. We then delve into a case report to explore sexual dimorphism of the C2 vertebrae. Moreover, we discuss some of these studies that showed a significant correlation between the dimensions of the second cervical vertebrae and height, suggesting that the C2 can be used as a reliable indicator for stature estimation. The high accuracy rate of sex estimation using the second cervical vertebrae suggests that this method is a valuable tool for forensic anthropologists. Its practical application can significantly contribute to identifying and profiling individuals in a forensic context, thereby aiding in the identification process.

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Continual re-evaluation of standards for forensic anthropological analyses are necessary, particularly as new methods are explored or as populations change. Indian South Africans are not a new addition to the South African population; however, a paucity of skeletal material is available for analysis from medical school collections, which has resulted in a lack of information on the sexual dimorphism in the crania. For comparable data, computed tomography scans of modern Black, Coloured and White South Africans were included in addition to Indian South Africans. Four cranial morphoscopic traits, were assessed on 408 modern South Africans (equal sex and population distribution). Frequencies, Chi-squared tests, binary logistic regression and random forest modelling were used to assess the data. Males were more robust than females for all populations, while White South African males were the most robust, and Black South African females were the most gracile. Population differences were noted among most groups for at least two variables, necessitating the creation of populations-specific binary logistic regression equations. Only White and Coloured South Africans were not significantly different. Indian South Africans obtained the highest correct classifications for binary logistic regression (94.1%) and random forest modelling (95.7%) and Coloured South Africans had the lowest correct classifications (88.8% and 88.0%, respectively). This study provides a description of the patterns of sexual dimorphism in four cranial morphoscopic traits in the current South African population, as well as binary logistic regression functions for sex estimation of Black, Coloured, Indian and White South Africans.

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SUMMARY: The study aims to demonstrate the success of deep learning methods in sex prediction using hyoid bone. The images of people aged 15-94 years who underwent neck Computed Tomography (CT) were retrospectively scanned in the study. The neck CT images of the individuals were cleaned using the RadiAnt DICOM Viewer (version 2023.1) program, leaving only the hyoid bone. A total of 7 images in the anterior, posterior, superior, inferior, right, left, and right-anterior-upward directions were obtained from a patient's cut hyoid bone image. 2170 images were obtained from 310 hyoid bones of males, and 1820 images from 260 hyoid bones of females. 3990 images were completed to 5000 images by data enrichment. The dataset was divided into 80 % for training, 10 % for testing, and another 10 % for validation. It was compared with deep learning models DenseNet121, ResNet152, and VGG19. An accuracy rate of 87 % was achieved in the ResNet152 model and 80.2 % in the VGG19 model. The highest rate among the classified models was 89 % in the DenseNet121 model. This model had a specificity of 0.87, a sensitivity of 0.90, an F1 score of 0.89 in women, a specificity of 0.90, a sensitivity of 0.87, and an F1 score of 0.88 in men. It was observed that sex could be predicted from the hyoid bone using deep learning methods DenseNet121, ResNet152, and VGG19. Thus, a method that had not been tried on this bone before was used. This study also brings us one step closer to strengthening and perfecting the use of technologies, which will reduce the subjectivity of the methods and support the expert in the decision-making process of sex prediction.

El estudio tuvo como objetivo demostrar el éxito de los métodos de aprendizaje profundo en la predicción del sexo utilizando el hueso hioides. En el estudio se escanearon retrospectivamente las imágenes de personas de entre 15 y 94 años que se sometieron a una tomografía computarizada (TC) de cuello. Las imágenes de TC del cuello de los individuos se limpiaron utilizando el programa RadiAnt DICOM Viewer (versión 2023.1), dejando solo el hueso hioides. Se obtuvieron un total de 7 imágenes en las direcciones anterior, posterior, superior, inferior, derecha, izquierda y derecha-anterior-superior a partir de una imagen seccionada del hueso hioides de un paciente. Se obtuvieron 2170 imágenes de 310 huesos hioides de hombres y 1820 imágenes de 260 huesos hioides de mujeres. Se completaron 3990 imágenes a 5000 imágenes mediante enriquecimiento de datos. El conjunto de datos se dividió en un 80 % para entrenamiento, un 10 % para pruebas y otro 10 % para validación. Se comparó con los modelos de aprendizaje profundo DenseNet121, ResNet152 y VGG19. Se logró una tasa de precisión del 87 % en el modelo ResNet152 y del 80,2 % en el modelo VGG19. La tasa más alta entre los modelos clasificados fue del 89 % en el modelo DenseNet121. Este modelo tenía una especificidad de 0,87, una sensibilidad de 0,90, una puntuación F1 de 0,89 en mujeres, una especificidad de 0,90, una sensibilidad de 0,87 y una puntuación F1 de 0,88 en hombres. Se observó que se podía predecir el sexo a partir del hueso hioides utilizando los métodos de aprendizaje profundo DenseNet121, ResNet152 y VGG19. De esta manera, se utilizó un método que no se había probado antes en este hueso. Este estudio también nos acerca un paso más al fortalecimiento y perfeccionamiento del uso de tecnologías, que reducirán la subjetividad de los métodos y apoyarán al experto en el proceso de toma de decisiones de predicción del sexo.

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Klales et al. (2012) is a popular standard for the estimation of skeletal sex. Since its publication, a number of studies have demonstrated that population-specific applications of Klales improve classification accuracy. However, it has also been shown that age appears to affect the expression of dimorphism in the pelvis across the lifespan. As such, the present study examines the accuracy of Klales, and the modified global standard of Kenyhercz et al. (2017), in a contemporary Indonesian population, including quantifying the effect of age. Pelvic multi-slice CT scans of 378 individuals (213 female; 165 male) were analysed in OsiriX®. Both standards were tested and Indonesian-specific models thereafter derived.When applied to the Indonesian sample, both the Klales and Kenyhercz standards resulted in lower classification accuracy relative to the original studies. In considering the Indonesian-specific models, the ventral arc was the most accurate for the classification of sex, at 93.3% with a - 3.0% sex bias. The accuracy of the three-trait model was 94.4%, with a - 5.5% sex bias. Age was shown to significantly affect the distribution of pelvic trait scores. As such, age-dependent models were also derived, with the standard for individuals between 30 and 49 years the most accurate, at 93.1% and a sex bias of - 4.0%. Accuracy was lower in individuals aged ≥ 50 years, at 91.3% and a sex bias of 4.1%. These findings support the importance of establishing population-specific standards and to facilitate improved accuracy and capabilities for forensic practitioners in Indonesia.

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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.

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BACKGROUND & OBJECTIVE: Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex estimation. Due to the complex nature of sex estimation, several studies have been conducted using different machine learning algorithms to improve the accuracy of sex prediction from anatomical measurements. MATERIAL & METHODS: In this study, linear data of the maxillary sinus in the population of northwest China by using Cone-Beam Computed Tomography (CBCT) were collected and utilized to develop logistic, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and random forest (RF) models for sex estimation with R 4.3.1. CBCT images from 477 samples of Han population (75 males and 81 females, aged 5-17 years; 162 males and 159 females, aged 18-72) were used to establish and verify the model. Length (MSL), width (MSW), height (MSH) of both the left and right maxillary sinuses and distance of lateral wall between two maxillary sinuses (distance) were measured. 80% of the data were randomly picked as the training set and others were testing set. Besides, these samples were grouped by age bracket and fitted models as an attempt. RESULTS: Overall, the accuracy of the sex estimation for individuals over 18 years old on the testing set was 77.78%, with a slightly higher accuracy rate for males at 78.12% compared to females at 77.42%. However, accuracy of sex estimation for individuals under 18 was challenging. In comparison to logistic, KNN and SVM, RF exhibited higher accuracy rates. Moreover, incorporating age as a variable improved the accuracy of sex estimation, particularly in the 18-27 age group, where the accuracy rate increased to 88.46%. Meanwhile, all variables showed a linear correlation with age. CONCLUSION: The linear measurements of the maxillary sinus could be a valuable tool for sex estimation in individuals aged 18 and over. A robust RF model has been developed for sex estimation within the Han population residing in the northwestern region of China. The accuracy of sex estimation could be higher when age is used as a predictive variable.

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INTRODUCTION: Identification is an important aspect of forensic medicine. Identification plays an imperative role, especially in highly decomposed bodies, mutilated bodies, and undisclosed and fragmentary human remains. The estimation of sex is an essential parameter of human identification. In forensic anthropometry, sex determination is related to morphometric characteristics of skeletal bones, such as the skull and mandible, clavicle, sternum, scapula, humerus, pelvic bone, sternum, and femur. Since teeth are decay-resistant, conscientious analysis of teeth can accredit reliable sex estimation of an individual, especially when other determinants are fragmented or destroyed. AIM: The aim of the study was to explore the association between sex and buccolingual crown dimensions of teeth. MATERIALS AND METHODS: The study sample consists of 100 volunteer subjects (50 male subjects and 50 female subjects) aged between 20 and 35 years. Alginate was used to take impressions of the teeth and the cast was prepared using pouring by dental stone. Measurements of buccolingual parameters of all the teeth (except the third molars) of both jaws were done on dental casts by using a digital caliper. RESULTS: Collected data were analyzed using SPSS software (IBM Corp., Armonk, NY) and were outlined as mean and standard deviation (SD). The male and female groups were compared using an independent Student's t-test or unpaired test. The results of this study revealed that 16 out of 28 odontometric parameters (except third molar) of the two groups (male and female) were higher in the male group as compared to the female group (p < 0.05). CONCLUSION: Buccolingual odontometric parameters can be used for sex estimation in the North Indian population.

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The biological profile estimation is the first step toward positive identification. However, it is not always possible to access a complete and well-preserved skeleton due to postmortem damage and taphonomic changes. As such, there is a need to develop new alternatives to analyze different bones of the human skeleton. The present study aims to analyze the patellar osteometry, with attention to its degree of sexual dimorphism, to establish a simple method for estimating sex in Portuguese adults. Six measurements were taken from 222 patella pairs, including 117 females and 105 males from the XXI Century Identified Skeleton Collection of the University of Coimbra. Subsequently, this method was validated in a different sample of 50 individuals equally representing both sexes. Maximum height stands out with a 77.0% of correct sex estimation, reaching 98.0% when applied to the new sample. The linear discriminant function analysis containing all the six variables showed the best results, with 80.2% of correct classification after cross-validation and 96.0% when applied to the independent sample.

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This review delves into the forensic utility of the sternum in creating a biological profile, focusing on sex, stature, and age estimation. Emphasizing the sternum's significance in challenging scenarios, the study supports the combined length of the manubrium and sternal body as a crucial indicator in sex and stature estimation. However, it highlights the need for caution in applying findings across diverse populations and questions the reliability of Hyrtl's law. Age estimation, primarily based on morphological changes and ossification ages, is explored, with one study showing promise but requiring further validation. While acknowledging the sternum's advantages, the review underscores potential limitations and the absence of specific studies on ancestry estimation, leaving this aspect open for future research. In conclusion, the review provides a comprehensive overview of the sternum's forensic applications, urging continued research to enhance accuracy and applicability.

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OBJECTIVE: This paper investigates whether deciduous upper molars and lower canines have sexual dimorphic features, exploring these teeth' dimensions and the presence of Zuckerkandl's tubercle and Carabelli's cusp on the first and second upper molars. DESIGN: We analyzed 64 pairs of dental plaster casts from 34 females and 30 males aged between 3 and 12 years. We measured the first and second deciduous upper molars and the lower deciduous canines (maximum mesiodistal and buccolingual length), and we registered the presence of the Zuckerkandl's tubercle and the Carabelli's cusp on the first and second upper molars, respectively. RESULTS: Regarding the differentiation between sexes using Carabelli's cusp and Zuckerkandl's tubercle, the classification was not independent of Carabelli's cusp presence only for tooth 65 (p = 0.035). In all other teeth, whether for Carabelli's cusp or Zuckerkandl's tubercle, their presence was similar for both sexes. There were statistically significant differences between sexes (p < 0.05) for the buccolingual measurements of both upper second molars, the first right upper molar, and the right canine. The developed model allowed for a 64.1% accuracy in sex estimation. CONCLUSIONS: The study suggests that while Carabelli's cusp and Zuckerkandl's tubercle in upper deciduous molars don't consistently differ between sexes, tooth size, particularly the buccolingual measurements of certain teeth, including upper deciduous molars and lower canines, may provide a more reliable criterion for sex estimation. The developed model depicted moderate accuracy, underscoring the need for a multifactorial approach when estimating sex from skeletal remains. It suggests that while dental features can contribute to sex estimation, they should be used in conjunction with other skeletal or molecular markers to improve accuracy.

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Chile had a violent military coup (1973-1990) that resulted in 3,000 victims declared detained, missing or killed; many are still missing and unidentified. Currently, the Human Rights Unit of the Forensic Medical Service in Chile applies globally recognised forensic anthropological approaches, but many of these methods have not been validated in a Chilean sample. As current research has demonstrated population-specificity with extant methods, the present study aims to validate sex estimation methods in a Chilean population and thereafter establish population-specific equations. A sample of 265 os coxae of known age and sex of adult Chileans from the Santiago Subactual Osteology Collection were analysed. Visual assessment and scoring of the pelvic traits were performed in accordance with the Phenice (1969) and Klales et al. (2012) methods. The accuracy of Phenice (1969) in the Chilean sample was 96.98%, with a sex bias of 7.68%. Klales et al. (2012) achieved 87.17% accuracy with a sex bias of -15.39%. Although both methods showed acceptable classification accuracy, the associated sex bias values are unacceptable in forensic practice. Therefore, six univariate and eight multivariate predictive models were formulated for the Chilean population. The most accurate univariate model was the ventral arc at 96.6%, with a sex bias of 5.2%. Classification accuracy using all traits was 97.0%, with a sex bias of 7.7%. This study provides Chilean practitioners a population-specific morphoscopic standard with associated classification probabilities acceptable to accomplish legal admissibility requirements in human rights and criminal cases specific to the second half of the 20th century.

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BACKGROUND: The increased use of virtual bone images in forensic anthropology requires a comprehensive study on the observational errors between dry bones and CT reconstructions. Here, we focus on the consistency of nonmetric sex estimation traits on the human skull. MATERIALS AND METHODS: We scored nine nonmetric traits on dry crania and mandibles (n = 223) of archaeological origin and their CT reconstructions. Additionally, we 3D surface scanned a subsample (n = 50) and repeated our observations. Due to the intricate anatomy of the mental eminence, we split it into two separate traits: the bilateral mental tubercles and the midsagittal mental protuberance. We provide illustrations and descriptions for both these traits. RESULTS: We obtained supreme consistency values between the CT and 3D surface modalities. The most consistent cranial traits were the glabella and the supraorbital margin, followed by the nuchal crest, zygomatic extension, mental tubercles, mental protuberance, mental eminence, mastoid process and ramus flexure, in descending order. The mental tubercles show higher consistency scores than the mental eminence and the mental protuberance. DISCUSSION: The increased interchangeability of the virtual modalities with each other as compared to the dry bone modality could be due to the lack of tactility on both the CT and surface scans. Moreover, tactility appears less essential with experience than a precise trait description. Future studies could revolve around the most consistent cranial traits, combining them with pelvic traits from a previous study, to test for accuracy.

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In forensic anthropology, osteological sex estimation methods are continuously reevaluated and updated to improve classification accuracies. Therefore, to gain a comprehensive understanding of recent trends in sex estimation research in forensic anthropology, a content analysis of articles published between 2000 and 2022 in Forensic Science International, the Journal of Forensic Sciences, the International Journal of Legal Medicine, the American Journal of Biological Anthropology, and Forensic Anthropology, was performed. The main goals of this content analysis were to (1) examine trends in metric versus morphological research, (2) examine which areas of the skeleton have been explored, (3) examine which skeletal collections and population affinities have been most frequently utilized, and (4) determine which statistical methods were commonly implemented. A total of 440 articles were coded utilizing MAXQDA and the resulting codes were exported for analysis. Statistical analyses were conducted utilizing the Cochran-Armitage and Jonckheere-Terpstra tests for trends, as well as Fisher-Freeman-Halton tests. The results demonstrate that sex estimation research published in these journals has prioritized metric over morphological methods. Further, the most utilized skeletal regions continue to be the skull and pelvis, while the most popular classification statistics continue to be discriminant function analysis and logistic regression. This study also demonstrates that a substantial portion of research has been conducted utilizing U.S. and Europe-based collections and limited populations. Based on these results, future sex estimation research must continue exploring the use of long bones and other postcranial elements, testing newer methods of analysis, as well as developing population-inclusive methods.

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