{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001313034,0.00009996234,0.0001078379,0.00006957351,0.0005322932,0.00006640504,0.001064178,0.00007008547,0.0000459393],"category_scores_gemma":[0.0001319898,0.00009436519,0.00007031084,0.0003130719,0.001222612,0.00001847927,0.0001354747,0.0001854419,0.000001126201],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003317527,"about_ca_system_score_gemma":0.02730636,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.68045,"about_ca_topic_score_gemma":0.9567807,"domain_scores_codex":[0.9980135,0.00002111218,0.0001987424,0.0003085538,0.0009425855,0.0005154906],"domain_scores_gemma":[0.9984449,0.00001207413,0.0001018528,0.0003734108,0.0006457967,0.0004220241],"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":[0.000004205851,0.00000693828,0.003405479,0.000006071234,0.00001980114,0.000004723424,0.00002031034,0.0001401548,0.01599567,0.0001636695,0.9732604,0.006972565],"study_design_scores_gemma":[0.001006346,0.0001889486,0.118964,0.00005073573,0.00002226092,0.0005445277,0.0008957587,0.002783049,0.1750345,0.001383392,0.6985543,0.0005721571],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878458,0.0008533506,0.0003448419,0.004435324,0.0005164123,0.0001073514,0.000323484,0.000002195969,0.005571259],"genre_scores_gemma":[0.9931977,0.00003004935,0.004180434,0.001016299,0.0005781096,9.513445e-7,0.0001003243,0.000008964845,0.000887177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2763307,"threshold_uncertainty_score":0.9782079,"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."}}