{"id":"W2591150033","doi":"10.1016/j.scijus.2017.02.005","title":"Sex estimation from the scapula in a contemporary Thai population: Applications for forensic anthropology","year":2017,"lang":"en","type":"article","venue":"Science & Justice","topic":"Forensic Anthropology and Bioarchaeology Studies","field":"Arts and Humanities","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"Chiang Mai University","keywords":"Sexing; Forensic anthropology; Population; Demography; Forensic science; Sample (material); Geography; Discriminant function analysis; Linear discriminant analysis; Biology; Statistics; Archaeology; Zoology; Sociology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.000472294,0.0001001959,0.0001599123,0.00005226934,0.005068698,0.0001049141,0.0005155162,0.00004613983,0.00009614884],"category_scores_gemma":[0.0003326781,0.00006649194,0.00003429244,0.00003972298,0.0422913,0.0003972076,0.0001610873,0.0001024067,0.00002104946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002634734,"about_ca_system_score_gemma":0.00008619619,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01747825,"about_ca_topic_score_gemma":0.04889237,"domain_scores_codex":[0.9991263,0.00002923755,0.0001857056,0.0002960357,0.0001163876,0.0002463677],"domain_scores_gemma":[0.9989693,0.0003213023,0.000167059,0.0004042983,0.0001109221,0.00002717161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002561591,0.00003125292,0.02048885,0.00001219356,0.00001141124,0.000001513607,0.0136062,0.00001136074,0.000005250969,0.9568398,0.002109819,0.006856705],"study_design_scores_gemma":[0.001919955,0.0004108816,0.1531339,0.0001006203,0.0003093418,0.00001428603,0.3570384,0.01936787,0.0003455777,0.4233604,0.04328976,0.0007090064],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.643163,0.002896099,0.02178461,0.2498161,0.01075096,0.004562831,0.0006087102,0.0002717364,0.06614596],"genre_scores_gemma":[0.9974405,0.0000169484,0.0008862282,0.0006216204,0.0004502783,0.0001148931,0.00003241385,0.000004855409,0.000432233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5334794,"threshold_uncertainty_score":0.9962265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08890245905994641,"score_gpt":0.3592263310866431,"score_spread":0.2703238720266967,"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."}}