{"id":"W3112702945","doi":"10.3138/cjccj.2020-0011","title":"Designing an Explainable Predictive Policing Model to Forecast Police Workforce Distribution in Cities","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut National de la Recherche Scientifique","funders":"","keywords":"Decision tree; Instinct; Computer science; Workforce; Intuition; Machine learning; Data science; Artificial intelligence; Criminology; Psychology; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001166788,0.0004298009,0.0004772539,0.0007453724,0.0004067152,0.0008439047,0.001001669,0.0009423385,0.001194713],"category_scores_gemma":[0.00442026,0.0005041471,0.0005544503,0.000545978,0.0003919272,0.0008497743,0.0006524514,0.0008862937,0.0001573149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001355315,"about_ca_system_score_gemma":0.001582029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03481327,"about_ca_topic_score_gemma":0.02451101,"domain_scores_codex":[0.9997043,0.00009761922,0.00001661641,0.00008489364,0.00002842529,0.00006810729],"domain_scores_gemma":[0.9983062,0.001128677,0.0002047578,0.0000688415,0.0002148149,0.00007663509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004095436,0.00003429876,0.009726045,0.00001826408,0.00001994495,0.00003089923,0.00009868697,0.9786943,0.0002451974,0.001711695,0.0003153601,0.00906432],"study_design_scores_gemma":[0.000003959551,0.000008976903,0.0009519364,0.000004048234,0.000005896738,0.00000373024,0.00001910556,0.9972742,0.00009230334,0.001534619,0.00009746638,0.000003782777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7114887,0.0001444325,0.2827153,0.001604729,0.00004607664,0.0001301657,0.000584855,0.0005045905,0.002781236],"genre_scores_gemma":[0.9711292,0.00008652611,0.02725269,0.00007750966,0.00001418392,0.0001049362,0.0003659955,0.00001804297,0.0009508904],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03481327,"threshold_uncertainty_score":0.06922126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2149799632941523,"score_gpt":0.3626272820463461,"score_spread":0.1476473187521938,"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."}}