{"id":"W3125918342","doi":"10.1111/caje.12204","title":"Crime, apprehension and clearance rates: Panel data evidence from Canadian provinces","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Waterloo","funders":"","keywords":"Apprehension; Commit; Property crime; Panel data; Crime rate; Economics; Econometrics; Demographic economics; Psychology; Criminology; Violent crime; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001073833,0.0001956354,0.0003847876,0.0004223516,0.0005094224,0.00028584,0.001132347,0.0001649379,0.001390208],"category_scores_gemma":[0.0008347813,0.0001874941,0.0001031244,0.00008535713,0.000456931,0.001584282,0.00004673295,0.0001996698,0.00004356686],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001955796,"about_ca_system_score_gemma":0.006240885,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9896101,"about_ca_topic_score_gemma":0.9999355,"domain_scores_codex":[0.9979959,0.000153707,0.0006277529,0.000459527,0.000005912447,0.0007572552],"domain_scores_gemma":[0.9956374,0.0003574647,0.0004027459,0.000558715,0.0002029845,0.002840705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002680824,0.00005071769,0.3540619,0.0001298673,0.0007247496,0.0007664831,0.02521249,0.0001478538,0.0004501556,0.315575,0.04717935,0.2554334],"study_design_scores_gemma":[0.001369894,0.0005509369,0.1567296,0.003171582,0.0002002822,0.0001900484,0.009120544,0.0007892558,0.0002169781,0.08073767,0.7454625,0.001460722],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985855,0.001377397,0.00006190014,0.0088867,0.001249611,0.0002140222,0.000837496,0.000005956111,0.001511935],"genre_scores_gemma":[0.9964516,0.001157806,0.0002572032,0.0004563455,0.0008079499,0.000004940803,0.00001165668,0.00002724645,0.0008252955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6982831,"threshold_uncertainty_score":0.9995227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.391517801141552,"score_gpt":0.2798971485958585,"score_spread":0.1116206525456936,"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."}}