{"id":"W4380355184","doi":"10.3138/cjccj.2022-0037","title":"Sizing up Crime and Weather Relationships in a Small Northern City","year":2023,"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":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"","keywords":"Negative binomial distribution; Criminology; Regression analysis; Bay; Population; Property crime; Poison control; Distribution (mathematics); Geography; Demography; Demographic economics; Violent crime; Psychology; Statistics; Sociology; Mathematics; Economics; Environmental health; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003384829,0.0002775866,0.0004670316,0.001116962,0.0009107554,0.0001693717,0.0004890303,0.0005013114,0.0001885633],"category_scores_gemma":[0.007000174,0.0003122604,0.0001376454,0.000267023,0.0009570066,0.0003057397,0.00006418997,0.001327218,0.00001535319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007944767,"about_ca_system_score_gemma":0.00255499,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09377073,"about_ca_topic_score_gemma":0.7762618,"domain_scores_codex":[0.9964249,0.0009631189,0.000656674,0.0003862545,0.00008846074,0.001480636],"domain_scores_gemma":[0.9962099,0.001578877,0.0003121293,0.000233182,0.0003568293,0.001309146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002586379,0.0001358268,0.1657151,0.002945663,0.0002445748,0.01018741,0.4661663,0.0004883793,0.0005314703,0.3119149,0.002975352,0.03843637],"study_design_scores_gemma":[0.0009037946,0.0003678782,0.4169888,0.00057319,0.003465714,0.002005351,0.5476508,0.0002864714,0.00003463685,0.01547009,0.01167793,0.000575361],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855648,0.001797037,0.0005478448,0.00575314,0.0006544612,0.0001681888,0.00002669176,0.00003905497,0.005448748],"genre_scores_gemma":[0.9960923,0.001238887,0.0006588059,0.0007425123,0.0002978253,0.00001614036,0.000007142854,0.00003296799,0.0009134683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6824911,"threshold_uncertainty_score":0.9999329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2515806165550096,"score_gpt":0.356857766125657,"score_spread":0.1052771495706474,"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."}}