{"id":"W16301130","doi":"","title":"The uses of offender profiling in the Canadian Criminal Justice system","year":2012,"lang":"en","type":"dissertation","venue":"UPT. Syiah Kuala University Library (Syiah Kuala University)","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Profiling (computer programming); Offender profiling; Suspect; Racial profiling; Criminal justice; Confidentiality; Criminology; Criminal investigation; Political science; Psychology; Law; Sociology; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01963121,0.0006283368,0.0008179153,0.02701489,0.02115849,0.0139817,0.003480704,0.001273753,0.003706802],"category_scores_gemma":[0.06042868,0.0005880648,0.0007071556,0.03324317,0.008003616,0.004012255,0.005908685,0.001802399,0.0002971842],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1413569,"about_ca_system_score_gemma":0.2231132,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9860708,"about_ca_topic_score_gemma":0.992274,"domain_scores_codex":[0.9622791,0.01029329,0.001997315,0.002107254,0.01996329,0.003359678],"domain_scores_gemma":[0.9303111,0.02005673,0.004959274,0.001931565,0.03921475,0.003526554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000176264,0.00006881803,0.09310851,0.006414222,0.0002391279,0.001596296,0.2432217,0.000871936,0.001327788,0.08553793,0.04526168,0.5221758],"study_design_scores_gemma":[0.00001946577,0.0001041129,0.2849999,0.01255589,0.0004056716,0.0007961616,0.2747922,0.001100232,0.001239591,0.006524842,0.417028,0.0004339573],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4270015,0.1092692,0.006387741,0.08514487,0.001333439,0.001320823,0.008688903,0.0002744713,0.360579],"genre_scores_gemma":[0.9143159,0.06328082,0.007283935,0.0038529,0.0001312623,0.0002901347,0.001402242,0.00008688144,0.009356063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8586432,"threshold_uncertainty_score":0.9959043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533559000113639,"score_gpt":0.2162861780990318,"score_spread":0.2009505880978954,"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."}}