{"id":"W4211243718","doi":"10.32920/ryerson.14655891","title":"Bayesian Crime Investigations: Integrating Actuarial and Expert Models","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"","keywords":"Overfitting; Bayesian probability; Sample (material); Regression; Computer science; Econometrics; Machine learning; Regression analysis; Field (mathematics); Artificial intelligence; Statistics; Mathematics; Artificial neural network","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":[0.03178922,0.001013404,0.001598957,0.002884066,0.0006348203,0.002874386,0.002161122,0.001533757,0.002541616],"category_scores_gemma":[0.09965297,0.0009606465,0.000846258,0.001437546,0.001026368,0.00425246,0.002207888,0.002340439,0.0005504261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001654379,"about_ca_system_score_gemma":0.001707255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01169343,"about_ca_topic_score_gemma":0.01416158,"domain_scores_codex":[0.9861718,0.01032636,0.0004450453,0.001085826,0.001680281,0.0002906358],"domain_scores_gemma":[0.9323658,0.05754293,0.003070226,0.003493881,0.002961156,0.0005660134],"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":[0.0003209137,0.0004605073,0.02935193,0.0001376956,0.0004185608,0.00008628417,0.0006528966,0.7489854,0.0003505307,0.05023273,0.001704284,0.1672983],"study_design_scores_gemma":[0.00001632689,0.00006120253,0.001829629,0.00003268668,0.00002865743,0.00001879264,0.00005223988,0.9697868,0.0001221645,0.02748758,0.0005421318,0.00002189223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1028406,0.0005282792,0.8848503,0.001964425,0.00007310746,0.0002319016,0.000145376,0.0006041544,0.008762009],"genre_scores_gemma":[0.7457886,0.0004350482,0.2502724,0.0004800688,0.000215834,0.0002123727,0.0002356657,0.00007242327,0.002287492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03178922,"threshold_uncertainty_score":0.1681194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1203458837964755,"score_gpt":0.3888209851218851,"score_spread":0.2684751013254096,"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."}}