{"id":"W3008847073","doi":"10.1016/j.forsciint.2020.110220","title":"Breaking the binary: The identification of trans-women in forensic anthropology","year":2020,"lang":"en","type":"article","venue":"Forensic Science International","topic":"Female Genital Mutilation/Cutting Issues","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Transgender; Feminization (sociology); Forehead; Forensic anthropology; Gender dysphoria; Psychology; Discriminant function analysis; Identification (biology); Chin; Medicine; Developmental psychology; Anatomy; Gender studies; Biology; Sociology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01771187,0.0004439741,0.0006298483,0.00320334,0.01030265,0.008238143,0.001680687,0.003146157,0.005255363],"category_scores_gemma":[0.03300359,0.000334808,0.0002278277,0.002640511,0.03096774,0.01277224,0.01145537,0.006169384,0.0005542962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00183032,"about_ca_system_score_gemma":0.004787064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006856618,"about_ca_topic_score_gemma":0.0134928,"domain_scores_codex":[0.9902391,0.007315407,0.0002955659,0.0005417401,0.0009195663,0.0006885194],"domain_scores_gemma":[0.9910656,0.004906434,0.001242016,0.001029929,0.001028661,0.0007273023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001113301,0.00006768195,0.02820656,0.0003230727,0.00002038204,0.001169548,0.5379984,0.00005629625,0.001077474,0.2817035,0.01230107,0.1369647],"study_design_scores_gemma":[0.000005812273,0.00005129727,0.01193867,0.00169964,0.00002125184,0.003135285,0.7223569,0.0002640979,0.0009274551,0.1591493,0.100407,0.00004321855],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5548591,0.04177504,0.02372371,0.2273026,0.003117477,0.0001714961,0.0001772764,0.00005467685,0.1488186],"genre_scores_gemma":[0.9647883,0.007058187,0.006135778,0.01350804,0.0005200233,0.0001310936,0.00005454974,0.00005488249,0.00774926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01771187,"threshold_uncertainty_score":0.09367043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03145842044337232,"score_gpt":0.3261011687719949,"score_spread":0.2946427483286226,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}