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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

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Abstract

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.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Acsádi G, Nemeskéri J (1970) History of human life span and mortality. Akademiai Kiado, Budapest

    Google Scholar 

  2. Anonymous (2010) Sex assessment. Scientific Working Group for Forensic Anthropology (SWGANTH). Retrieved from https://www.nist.gov/system/files/documents/2018/03/13/swganth_sex_assessment.pdf

  3. Anonymous (2020) Australia New Zealand Policing Advisory Agency, Guidelines for Forensic Anthropology Practitioners (ANZPAA). Version 2.0. Retrieved from https://www.anzpaa.org.au/ArticleDocuments/2304/Guidelines%20for%20Forensic%20Anthropology%20%20Practitioners%20-%20March%202020.pdf.aspx

  4. Attia MH, Attia MH, Farghaly YT et al (2022a) Performance of the supervised learning algorithms in sex estimation of the proximal femur: a comparative study in contemporary Egyptian and Turkish samples. Sci Justice 62:288–309. https://doi.org/10.1016/j.scijus.2022.03.003

    Article  Google Scholar 

  5. Attia MH, Kholief MA, Zaghloul NM et al (2022b) Efficiency of the Adjusted Binary Classification (ABC) approach in osteometric sex estimation: a comparative study of different linear machine learning algorithms and training sample sizes. Biology (Basel) 11:917

    PubMed  Google Scholar 

  6. Avent PR, Hughes CE, Garvin HM (2022) Applying posterior probability informed thresholds to traditional cranial trait sex estimation methods. J Forensic Sci 67:440–449. https://doi.org/10.1111/1556-4029.14947

    Article  PubMed  Google Scholar 

  7. Bareša T, Jerković I, Bašić Ž et al (2024) Walker’s traits for sex estimation in modern Croatian population using MSCT virtual cranial database: validation and development of population-specific standards. Forensic Imaging 36:200578. https://doi.org/10.1016/j.fri.2024.200578

    Article  Google Scholar 

  8. Bartholdy BP, Sandoval E, Hoogland MLP, Schrader SA (2020) Getting rid of dichotomous sex estimations: why logistic regression should be preferred over discriminant function analysis. J Forensic Sci 65:1685–1691. https://doi.org/10.1111/1556-4029.14482

    Article  PubMed  PubMed Central  Google Scholar 

  9. Baumgarten SE, Kenyon-Flatt B (2020) Metric methods for estimating sex utilizing the pelvis. In: Klales A (ed) Sex estimation of the human skeleton. Academic Press, pp 171–184

    Chapter  Google Scholar 

  10. Bertsatos A, Chovalopoulou ME, Brůžek J, Bejdová Š (2020) Advanced procedures for skull sex estimation using sexually dimorphic morphometric features. Int J Legal Med 134:1927–1937

    Article  PubMed  Google Scholar 

  11. Bertsatos A, Christaki A, Chovalopoulou ME (2019) Testing the reliability of 3D-ID software in sex and ancestry estimation with a modern Greek sample. Forensic Sci Int 297:132–137

    Article  PubMed  Google Scholar 

  12. Boucherie A (2023) Analyse du dimorphisme sexuel de variables métriques de la base du crâne: intérêts archéo-anthropologiques et forensiques. Dissertation. Université Libre de Bruxelles

  13. Boyd C, Boyd D (2018) Forensic anthropology: theoretical framework and scientific basis. John Wiley & Sons, Hoboken

    Book  Google Scholar 

  14. Brennan EJ (2023) Differential adult mortality risk from late medieval to early modern Berlin: health consequences at the intersection of urban growth and climate change. Am J Biol Anthropol 180:21

    Google Scholar 

  15. Brůžek J, Murail P (2006) Methodology and reliability of sex determination from the skeleton. In: Schmitt A, Cunha E, Pinheiro J (eds) Forensic anthropology and medicine: complementary sciences from recovery to cause of death. Humana Press Inc., Totowa, pp 225–242

    Chapter  Google Scholar 

  16. Brůžek J, Santos F, Dutailly B et al (2017) Validation and reliability of the sex estimation of the human os coxae using freely available DSP2 software for bioarchaeology and forensic anthropology. Am J Phys Anthropol 164:440–449. https://doi.org/10.1002/ajpa.23282

    Article  PubMed  Google Scholar 

  17. Buikstra JE, Ubelaker DH (1994) Standards for data collection from human skeletal remains : proceedings of a seminar at the Field Museum of Natural History, organized by Jonathan Haas. Archeological Survey

  18. Byrnes JF, Torres SEM, Johnson LJ et al (2023) New tricks, old bones, reassessing assigned sex at birth estimations of the Erie County Poorhouse cemetery using MorphoPASSE. Am J Biol Anthropol 180:24

    Google Scholar 

  19. Cappella A, Bertoglio B, Di Maso M et al (2022) Sexual dimorphism of cranial morphological traits in an italian sample: a population-specific logistic regression model for predicting sex. Biology (Basel) 11:1202

    PubMed  Google Scholar 

  20. Cohen J (1968) Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit. Psychol Bull 70:213–220

    Article  CAS  PubMed  Google Scholar 

  21. Daubert v. Merrell Dow Pharmaceuticals (1993) Daubert v. Merrell Dow Pharmaceuticals

  22. Davidson M, Nakhaeizadeh S, Rando C (2023) Cognitive bias and the order of examination in forensic anthropological non-metric methods: a pilot study. Aust J Forensic Sci 55:255–271. https://doi.org/10.1080/00450618.2021.1998625

    Article  Google Scholar 

  23. Dirkmaat, Cabo LL (2012) Forensic anthropology: embracing the new paradigm. In: Dirkmaat DC (ed) A companion to forensic anthropology. Wiley, Ltd, pp 3–40

  24. Dror IE (2023) The most consistent finding in forensic science is inconsistency. J Forensic Sci 68:1851–1855. https://doi.org/10.1111/1556-4029.15369

    Article  PubMed  Google Scholar 

  25. Ferembach D, Schwidetzky I, Stloukal M (1980) Recommendations for age and sex diagnoses of skeletons. J Hum Evol 9:517–549

    Article  Google Scholar 

  26. Franklin D, Cardini A, Flavel A, Kuliukas A (2013) Estimation of sex from cranial measurements in a Western Australian population. Forensic Sci Int 229:158.e1-158.e8. https://doi.org/10.1016/j.forsciint.2013.03.005

    Article  PubMed  Google Scholar 

  27. Galeta P, Brůžek J (2020) Sex estimation using continuous variables: problems and principles of sex classification in the zone of uncertainty. In: Obertová Z, Stewart A, Cattaneo C (eds) Statistics and probability in forensic anthropology. Academic Press, pp 155–182

    Chapter  Google Scholar 

  28. Garvin (2020) Adult sex estimation from cranial morphological traits. In: Klales A (ed) Sex estimation of the human skeleton. Academic Press, pp 95–112

    Chapter  Google Scholar 

  29. Garvin HM, Uhl N, Passalacqua NV et al (2012) Developments in forensic anthropology: age at- death estimation. In: Dirkmaat DC (ed) A companion to forensic anthropology, first. Wiley-Blackwell, London, pp 202–223

    Chapter  Google Scholar 

  30. Garvin, Klales A (2020) Adult skeletal sex estimation and global standardization. In: Parra R, Zapico S, Ubelaker D (eds) Forensic science and humanitarian action: interacting with the dead and the living. Wiley, Ltd, pp 109–209

  31. Garvin, Sholts S, Mosca L (2014) Sexual dimorphism in human cranial trait scores: effects of population, age, and body size. Am J Phys Anthropol 154:259–269

    Article  PubMed  Google Scholar 

  32. Grabherr S, Cooper C, Ulrich-Bochsler S et al (2009) Estimation of sex and age of “virtual skeletons”-a feasibility study. Eur Radiol 19:419–429. https://doi.org/10.1007/s00330-008-1155-y

    Article  PubMed  Google Scholar 

  33. Grivas CR, Komar DA (2008) Kumho, Daubert, and the nature of scientific inquiry: Implications for forensic anthropology. J Forensic Sci 53:771–776

    Article  PubMed  Google Scholar 

  34. Guyomarc’h, Brůžek J (2011) Accuracy and reliability in sex determination from skulls: a comparison of Fordisc® 3.0 and the discriminant function analysis. Forensic Sci Int 208:180-e1

    Article  Google Scholar 

  35. Jantz RL, Ousley SD (2005) FORDISC 3: computerized forensic discriminant functions. Version 3.0. The University of Tennessee, Knoxville

  36. Jerković I, Bašić Ž, Anđelinović Š, Kružić I (2020) Adjusting posterior probabilities to meet predefined accuracy criteria: a proposal for a novel approach to osteometric sex estimation. Forensic Sci Int 311:110273. https://doi.org/10.1016/j.forsciint.2020.110273

    Article  CAS  PubMed  Google Scholar 

  37. Jerković I, Bašić Ž, Kružić I, Anđelinović Š (2018) Creating reference data on sex for ancient populations using the Probabilistic Sex Diagnosis method: a validation test using the results of aDNA analysis. J Archaeol Sci 94:44–50

    Article  Google Scholar 

  38. Jilala W, Ng’walali P, Russa D, Bushozi P (2021) Sexing contemporary Tanzanian skeletonized remains using skull morphology: a test of the walker sex assessment method. Forensic Sci Int Rep 3:100195. https://doi.org/10.1016/j.fsir.2021.100195

    Article  Google Scholar 

  39. Klales A (2020a) MorphoPASSE: morphological pelvis and skull sex estimation program. In: Klales A (ed) Sex estimation of the human skeleton. Academic Press, pp 271–278

    Chapter  Google Scholar 

  40. Klales A (2018a) MorphoPASSE: the morphological pelvis and skull sex estimation database. Version 1.0. Washburn, University, Topeka

  41. Klales A (2020b) Practitioner preferences for sex estimation from human skeletal remains. In: Klales A (ed) Sex Estimation of the Human Skeleton. Academic Press, pp 11–23

    Chapter  Google Scholar 

  42. Klales A, Cole S (2018) MorphoPASSE: the morphological pelvis and skull sex estimation database manual. Version 1.0. Washburn, University, Topeka

  43. Klales AR (2018b) Introducing MorphoPASSE: the morphological pelvis and skull sex estimation database. In: Proceedings of the 70th Annual Scientific Meeting of the American Academy of Forensic Sciences in Seattle. Wa

  44. Klales AR, Ousley SD, Vollner JM (2012) A revised method of sexing the human innominate using Phenice’s nonmetric traits and statistical methods. Am J Phys Anthropol 149:104–114

    Article  PubMed  Google Scholar 

  45. Kotěrová A, Rmoutilová R, Brůžek J (2022) Current trends in methods for estimating age and sex from the adult human skeleton. Anthropologie 60:225–252

    Article  Google Scholar 

  46. Kotěrová A, Velemínská J, Dupej J et al (2016) Disregarding population specificity: its influence on the sex assessment methods from the tibia. Int J Legal Med 131:251–261

    Article  PubMed  Google Scholar 

  47. Kranioti EF, Apostol MA (2014) Sexual dimorphism of the tibia in contemporary Greeks, Italians, and Spanish: forensic implications. Int J Legal Med 129:357–363. https://doi.org/10.1007/s00414-014-1045-6

    Article  PubMed  Google Scholar 

  48. Krishan K, Chatterjee PM, Kanchan T et al (2016) A review of sex estimation techniques during examination of skeletal remains in forensic anthropology casework. Forensic Sci Int 261:165.e1-165.e8

    Article  PubMed  Google Scholar 

  49. Krüger GC, L’Abbé EN, Stull KE, Kenyhercz MW (2015) Sexual dimorphism in cranial morphology among modern South Africans. Int J Legal Med 129:869–875. https://doi.org/10.1007/s00414-014-1111-0

    Article  PubMed  Google Scholar 

  50. Lesciotto K (2015) The impact of Daubert on the admissibility of forensic anthropology expert testimony. J Forensic Sci 60:549–555

    Article  PubMed  Google Scholar 

  51. Lewis, Garvin HM (2016) Reliability of the Walker cranial nonmetric method and implications for sex estimation. J Forensic Sci 61:743–751

    Article  PubMed  Google Scholar 

  52. Liebenberg L, Krüger GC, L’Abbé EN, Stull KE (2019) Postcraniometric sex and ancestry estimation in South Africa: a validation study. Int J Legal Med 133:289–296. https://doi.org/10.1007/s00414-018-1865-x

    Article  PubMed  Google Scholar 

  53. Lye R, Obertová Z, Bachtiar NA, Franklin D (2024) Validating the use of clinical MSCT scans for cranial nonmetric sex estimation in a contemporary Indonesian population. Int J Legal Med. https://doi.org/10.1007/s00414-024-03176-5

    Article  PubMed  Google Scholar 

  54. Morrison GS, Weber P, Basu N et al (2021) Calculation of likelihood ratios for inference of biological sex from human skeletal remains. Forensic Sci Int Synerg 3:100202. https://doi.org/10.1016/j.fsisyn.2021.100202

    Article  PubMed  PubMed Central  Google Scholar 

  55. Murail P, Brůžek J, Houët F, Cunha E (2005) DSP: a tool for probabilistic sex diagnosis using worldwide variability in hip-bone measurements. Bull Mém Soc Anthropol Paris 17:167–176

    Article  Google Scholar 

  56. Nikita E, Michopoulou E (2018) A quantitative approach for sex estimation based on cranial morphology. Am J Phys Anthropol 165:507–517

    Article  PubMed  Google Scholar 

  57. Oikonomopoulou EK, Valakos E, Nikita E (2017) Population-specificity of sexual dimorphism in cranial and pelvic traits: evaluation of existing and proposal of new functions for sex assessment in a Greek assemblage. Int J Legal Med 131:1731–1738

    Article  PubMed  Google Scholar 

  58. Phenice T (1969) A newly developed visual method of sexing the os pubis. Am J Phys Anthropol 30:297–301

    Article  CAS  PubMed  Google Scholar 

  59. R Core Team (2023) R: a language and environment for statistical computing

  60. Ramsthaler F, Kreutz K, Verhoff MA (2007) Accuracy of metric sex analysis of skeletal remains using Fordisc® based on a recent skull collection. Int J Legal Med 121:477–482

    Article  CAS  PubMed  Google Scholar 

  61. Santos F (2021) rdss: an R package to facilitate the use of Murail et al’.s (1999) approach of sex estimation in past populations. Int J Osteoarchaeol 31:382–392

    Article  Google Scholar 

  62. Slice DE, Ross A (2009) 3D-ID: geometric morphometric classification of crania for forensic scientists. Proc Natl Acad Sci USA 106:2124–2129

    PubMed  PubMed Central  Google Scholar 

  63. Stevenson JC, Mahoney ER, Walker PL, Everson PM (2009) Prediction of sex based on five skull traits using decision analysis (CHAID). Am J Phys Anthropol 139:434–441

    Article  PubMed  Google Scholar 

  64. Swift L, Obertova Z, Franklin D (2024) Demonstrating the empirical effect of population specificity of anthropological standards in a contemporary Australian population. Int J Legal Med 138:537–545. https://doi.org/10.1007/s00414-023-03031-z

    Article  PubMed  Google Scholar 

  65. Tallman S (2019) Cranial nonmetric sexual dimorphism and sex estimation in East and Southeast Asian individuals. Forensic Anthropol 4:204–221

    Google Scholar 

  66. Tallman SD, Go MC (2018) Application of the optimized summed scored attributes method to sex estimation in Asian Crania. J Forensic Sci 63:809–814. https://doi.org/10.1111/1556-4029.13644

    Article  PubMed  Google Scholar 

  67. Ubelaker DH, DeGaglia CM (2017) Population variation in skeletal sexual dimorphism. Forensic Sci Int 278:407.e1-407.e7. https://doi.org/10.1016/j.forsciint.2017.06.012

    Article  PubMed  Google Scholar 

  68. Ubelaker DH, Ross AH, Graver SM (2002) Application of forensic discriminant functions to a Spanish cranial sample. Forensic Sci Commun 4(3). Retrieved from https://archives.fbi.gov/archives/about-us/lab/forensic-science-communications/fsc/july2002/ubelaker1.htm

  69. Urbanová P, Ross AH, Jurda M, Nogueira MI (2014) Testing the reliability of software tools in sex and ancestry estimation in a multi-ancestral Brazilian sample. Leg Med 16:264–273

    Article  Google Scholar 

  70. Vargas DS, St John ME, Garcia-Bernabe JR, DiGangi EA (2022) MorphoPASSE skull sexing error. Am J Biol Anthropol 177:159–160

    Google Scholar 

  71. Walker PL (2008) Sexing skulls using discriminant function analysis of visually assessed traits. Am J Phys Anthropol 136:39–50. https://doi.org/10.1002/ajpa.20776

    Article  PubMed  Google Scholar 

  72. Walrath D, Turner P, Bruzek J (2004) Reliability test of the visual assessment of cranial traits for sex determination. Am J Phys Anthr 125:132–137

    Article  Google Scholar 

  73. Williams BA, Rogers TL (2006) Evaluating the accuracy and precision of cranial morphological traits for sex determination. J Forensic Sci 51:729–735. https://doi.org/10.1111/j.1556-4029.2006.00177.x

    Article  PubMed  Google Scholar 

  74. Wright R (2012) Guide to using the CRANID programs Cr6bInd: for linear and nearest neighbours discriminants analysis. Retrieved from http://www.box.net/shared/static/qyaq6thdds.pdf

  75. Zejdlik K, Nyárádi Z, Gonciar A (2021) Evidence of horsemanship in two Szekler noblemen from the Baroque period. Int J Osteoarchaeol 31:66–76

    Article  Google Scholar 

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Correspondence to Anežka Pilmann Kotěrová.

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The use of CT was approved by the ethical board of the Faculty of Science, Charles University in Prague, Czech Republic, the Medical Faculty, Aix-Marseille University, France, and the Alexandria Faculty of Medicine Ethical Committee in Egypt (ethical approval serial number 0306062, IRB NO: 00012098 -FWA NO: 00018699).

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Pilmann Kotěrová, A., Santos, F., Bejdová, Š. et al. 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. Int J Legal Med (2024). https://doi.org/10.1007/s00414-024-03215-1

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