{"id":"W1969825806","doi":"10.1080/00085030.2006.10757135","title":"Canada's National DNA Data Bank: A Success Story","year":2006,"lang":"en","type":"article","venue":"Canadian Society of Forensic Science Journal","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Crime scene; Sexual assault; Data bank; Matching (statistics); Criminology; History; Genealogy; Geography; Psychology; Computer science; Medicine; Poison control; Medical emergency; Injury prevention; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.03943847,0.001870663,0.001637764,0.006413747,0.01967509,0.02051576,0.007285765,0.01323146,0.01030737],"category_scores_gemma":[0.06805532,0.001492029,0.001370759,0.01240574,0.01147938,0.01163898,0.006357028,0.0171419,0.004245389],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1093695,"about_ca_system_score_gemma":0.3266304,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9839866,"about_ca_topic_score_gemma":0.9845465,"domain_scores_codex":[0.9542705,0.002621304,0.001813816,0.002545818,0.03360406,0.005144295],"domain_scores_gemma":[0.857594,0.01570828,0.001922507,0.003918226,0.09207381,0.02878318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001248624,0.00006592895,0.005489918,0.0002165716,0.0000424682,0.000326278,0.0005655019,0.000219215,0.0002068118,0.02046266,0.9264849,0.04579486],"study_design_scores_gemma":[0.0000641908,0.00003351902,0.01155229,0.0005616553,0.00004084233,0.0002033399,0.001242581,0.0005799977,0.0002797713,0.003847821,0.9814944,0.00009956166],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004147222,0.02364977,0.001182595,0.9262411,0.007109369,0.0001201137,0.01006382,0.0004462081,0.02703985],"genre_scores_gemma":[0.1455299,0.1006567,0.02163936,0.5593243,0.008571565,0.0003974074,0.04924435,0.001667375,0.112969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8906305,"threshold_uncertainty_score":0.7935349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875382374869135,"score_gpt":0.2744300755352301,"score_spread":0.2556762517865388,"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."}}