{"id":"W2037839031","doi":"10.1111/j.1556-4029.2007.00456.x","title":"Bioinformatics and Human Identification in Mass Fatality Incidents: The World Trade Center Disaster*","year":2007,"lang":"en","type":"article","venue":"Journal of Forensic Sciences","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Institute of Justice","keywords":"Identification (biology); Software; Computer science; Data science; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003982784,0.0003840022,0.0005851692,0.001941157,0.0009589865,0.001807093,0.0007907844,0.0008739287,0.001597068],"category_scores_gemma":[0.01083556,0.0002865471,0.0005331269,0.002396179,0.0005388732,0.0009955993,0.00127519,0.0007628179,0.001178321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006841456,"about_ca_system_score_gemma":0.001544915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003444416,"about_ca_topic_score_gemma":0.004587947,"domain_scores_codex":[0.9975666,0.001314698,0.0001983527,0.0004163463,0.0003902056,0.0001138852],"domain_scores_gemma":[0.9941192,0.004113695,0.0005587934,0.0003585543,0.0005604907,0.0002892672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002323774,0.0009963888,0.224869,0.001261943,0.0002777214,0.003249396,0.004334126,0.03586647,0.02909486,0.01235596,0.04967185,0.6356986],"study_design_scores_gemma":[0.0002383886,0.0008743813,0.2652455,0.0005475996,0.0002511843,0.004882117,0.006766965,0.5269299,0.0296312,0.05130559,0.1130869,0.0002402662],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5428181,0.004451714,0.3908391,0.01759749,0.0003725367,0.0009283891,0.01009392,0.01695995,0.01593872],"genre_scores_gemma":[0.6345561,0.001867092,0.3493712,0.001593331,0.0002114954,0.0004947772,0.009040456,0.0004879586,0.002377623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003982784,"threshold_uncertainty_score":0.02106321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0248920957696135,"score_gpt":0.341916123633467,"score_spread":0.3170240278638535,"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."}}