{"id":"W4311955347","doi":"10.1093/acrefore/9780190264079.013.814","title":"Calculating Crime Rates","year":2022,"lang":"en","type":"reference-entry","venue":"Oxford Research Encyclopedia of Criminology and Criminal Justice","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Demographics; Crime rate; Population; Criminology; Population size; Dark figure of crime; Geography; Demography; Demographic economics; Economics; Psychology; Sociology","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":[0.00228844,0.001095111,0.0005327236,0.01468506,0.0006228651,0.002186484,0.001155037,0.0004949452,0.03079526],"category_scores_gemma":[0.01795502,0.0004399027,0.00110123,0.008384749,0.0003909063,0.001606078,0.00121679,0.001055666,0.0215181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009769701,"about_ca_system_score_gemma":0.00140876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01075663,"about_ca_topic_score_gemma":0.008100831,"domain_scores_codex":[0.9962485,0.0008839745,0.0005126763,0.000628831,0.001540591,0.0001854071],"domain_scores_gemma":[0.9925326,0.001805808,0.0009420631,0.0009374829,0.003483993,0.000298138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001227569,0.0001156507,0.1257239,0.001184407,0.0002523843,0.0002257488,0.001929992,0.004459201,0.000902924,0.05121939,0.2149925,0.5988712],"study_design_scores_gemma":[0.00004310712,0.0002760568,0.2363929,0.001626228,0.0002385202,0.001474647,0.003128279,0.01431511,0.006224932,0.03414621,0.7019247,0.0002092993],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1223304,0.004065382,0.2097857,0.001971463,0.002247681,0.003161613,0.2051094,0.00804989,0.4432785],"genre_scores_gemma":[0.385325,0.006835228,0.2831864,0.000493978,0.000648364,0.005607991,0.1763553,0.00202087,0.1395268],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03079526,"threshold_uncertainty_score":0.1030204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2030264610764117,"score_gpt":0.4546323135779496,"score_spread":0.2516058525015379,"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."}}