{"id":"W149485883","doi":"10.1038/77173","title":"The promise and perils of criminal DNA databanking","year":2000,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computational biology; Criminology; Biology; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001583497,0.00008195216,0.00008734304,0.00002809559,0.00009840421,0.000009760331,0.0002485429,0.0005760686,0.00003168759],"category_scores_gemma":[0.0001023012,0.00005497896,0.00002811446,0.00007600128,0.0005701147,0.000001178733,0.0001192236,0.0002928673,0.000003341876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002681001,"about_ca_system_score_gemma":0.00003629117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000448221,"about_ca_topic_score_gemma":0.00001803758,"domain_scores_codex":[0.9993369,0.00002478614,0.000109309,0.0002364952,0.00009313858,0.0001993643],"domain_scores_gemma":[0.9994923,0.00001321004,0.0000284878,0.000403493,0.0000366603,0.00002583697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001493701,0.00001596626,0.0001394628,0.00001587213,0.00002949545,0.000002808476,0.0000192245,7.575258e-7,0.6049916,0.001847737,0.002431803,0.3903559],"study_design_scores_gemma":[0.0002151118,0.0002297252,0.001053011,0.000006087907,0.000008273108,0.00005261707,0.00006106661,0.0000155569,0.6255657,0.0002398859,0.3724836,0.00006931329],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788948,0.01834791,0.00002343799,0.001432917,0.00005116624,0.0001266187,0.00001031195,0.0000101122,0.001102724],"genre_scores_gemma":[0.9915355,0.006657655,0.0006512204,0.00009136516,0.00006772835,0.000006974234,0.00001934519,0.000008725642,0.000961417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3902866,"threshold_uncertainty_score":0.4443169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004820087461587132,"score_gpt":0.2634957377897514,"score_spread":0.2586756503281643,"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."}}