{"id":"W3155930012","doi":"10.1002/bsl.2513","title":"Making sense of senseless murders: The who, what, when, and where?","year":2021,"lang":"en","type":"article","venue":"Behavioral Sciences & the Law","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Canadian Mounted Police; Simon Fraser University","funders":"","keywords":"Homicide; Criminology; Poison control; Commission; Human factors and ergonomics; Phenomenon; Empirical research; Suicide prevention; Injury prevention; Offender profiling; Occupational safety and health; Psychology; Sample (material); Process (computing); Computer security; Computer science; Medicine; Medical emergency; Political science; Law; Data mining; Mathematics","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":[0.004246248,0.0003178074,0.0003881055,0.001733832,0.001449669,0.003058994,0.0007956014,0.0007231533,0.0007719679],"category_scores_gemma":[0.03020756,0.0002514595,0.0002174745,0.0006472341,0.00589584,0.002973798,0.003391254,0.001459652,0.0000885754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008324549,"about_ca_system_score_gemma":0.001334444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001523815,"about_ca_topic_score_gemma":0.003389216,"domain_scores_codex":[0.99681,0.002064012,0.0002244744,0.000233379,0.0003799085,0.0002881654],"domain_scores_gemma":[0.9837334,0.006098217,0.007333248,0.0009262887,0.000920561,0.0009883668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001329209,0.0002066125,0.5006403,0.0003153501,0.00006703851,0.001478223,0.3955031,0.0001007482,0.00090817,0.008501093,0.001387797,0.09075852],"study_design_scores_gemma":[0.00001023718,0.0001583833,0.2894466,0.0004738591,0.00003673643,0.002202202,0.6930556,0.0005203093,0.000492329,0.00798757,0.005557702,0.00005848135],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952414,0.000625365,0.0009205109,0.00130322,0.00002655104,0.00002332682,0.00001689631,0.000003965335,0.001838694],"genre_scores_gemma":[0.9991552,0.0002768914,0.0002969101,0.0001121676,0.000009141699,0.00001051612,0.000008761931,0.000001408823,0.0001289992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004246248,"threshold_uncertainty_score":0.02245659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2036414774832289,"score_gpt":0.4448993018854404,"score_spread":0.2412578244022115,"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."}}