{"id":"W2910524267","doi":"10.1109/iemcon.2018.8614828","title":"Crime Analysis Through Machine Learning","year":2018,"lang":"en","type":"article","venue":"","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":167,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fraser Institute; Simon Fraser University","funders":"","keywords":"Decision tree; Computer science; Machine learning; Artificial intelligence; Crime analysis; Work (physics); Random forest; Criminology; Engineering; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001560224,0.0007642676,0.0007734593,0.006784928,0.000486216,0.002614917,0.0007296181,0.0005046437,0.001837535],"category_scores_gemma":[0.007973913,0.0002512407,0.0006584922,0.004097224,0.0006885408,0.001508816,0.0008992741,0.0008634075,0.0008648995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283489,"about_ca_system_score_gemma":0.001632375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01937795,"about_ca_topic_score_gemma":0.01779586,"domain_scores_codex":[0.9983354,0.0006730654,0.0001028756,0.0002501201,0.0005347575,0.0001038596],"domain_scores_gemma":[0.9968631,0.001700181,0.000445603,0.0003821162,0.0005515229,0.00005740148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001082957,0.0005548741,0.1365984,0.000430765,0.0005185184,0.0001902814,0.0003434934,0.1989175,0.001069397,0.03125925,0.009918434,0.6200908],"study_design_scores_gemma":[0.0000109263,0.00009257041,0.04276013,0.0002592334,0.0000671761,0.000132482,0.0004549135,0.9071729,0.002948447,0.03608666,0.009959928,0.00005456214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2896197,0.004597015,0.6527053,0.004120023,0.0002729621,0.0005295967,0.006718738,0.003011889,0.03842485],"genre_scores_gemma":[0.8565688,0.002038316,0.1345679,0.0001595767,0.0001040495,0.0001676373,0.003510468,0.00005764056,0.002825623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01937795,"threshold_uncertainty_score":0.03853029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07580224534178513,"score_gpt":0.4188543972150707,"score_spread":0.3430521518732855,"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."}}