{"id":"W2305291328","doi":"10.1177/0306624x16632259","title":"Crime Seasonality: Examining the Temporal Fluctuations of Property Crime in Cities With Varying Climates","year":2016,"lang":"en","type":"article","venue":"International Journal of Offender Therapy and Comparative Criminology","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Property crime; Ordinary least squares; Negative binomial distribution; Geography; Seasonality; Property (philosophy); Econometrics; Violent crime; Criminology; Statistics; Mathematics; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004992731,0.00009588112,0.0002266917,0.0001312757,0.0001314759,0.00004518913,0.0003281961,0.00004042486,0.0004490776],"category_scores_gemma":[0.00005628579,0.00004364286,0.00006413807,0.00005721833,0.0006583171,0.0003285342,0.00003576094,0.0001263212,0.000001545029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000540874,"about_ca_system_score_gemma":0.0001359937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004158136,"about_ca_topic_score_gemma":0.0001450661,"domain_scores_codex":[0.9987048,0.0003399418,0.0003941701,0.0001101051,0.0003048283,0.0001461914],"domain_scores_gemma":[0.9985851,0.0004143192,0.0003372153,0.00006844908,0.0005585198,0.00003638312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002794246,0.001123499,0.4621274,0.00002728636,0.001908873,0.00006874647,0.1454721,0.00003533984,0.02664562,0.2580068,0.00199655,0.09979349],"study_design_scores_gemma":[0.004233529,0.001468005,0.904039,0.0006511983,0.00006667461,0.0001590033,0.04530505,0.00006078312,0.01064019,0.01445149,0.0186109,0.0003142159],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868089,0.0007730547,0.001605596,0.004270295,0.000281809,0.0001105058,0.00001111376,0.000005903191,0.006132812],"genre_scores_gemma":[0.9986989,0.0004183812,0.0002190164,0.0001814881,0.0001289691,0.000007518008,0.000001243276,0.000004135576,0.000340338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4419115,"threshold_uncertainty_score":0.4917085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4472244862477487,"score_gpt":0.4067212088170458,"score_spread":0.04050327743070287,"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."}}