{"id":"W7000946793","doi":"","title":"The Impact of Business Improvement Districts on Crime","year":2022,"lang":"en","type":"other","venue":"City Research Online (City University London)","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deterrence (psychology); Quarter (Canadian coin); Deterrence theory; Panel data; Set (abstract data type); Crime prevention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002164195,0.0002326229,0.0004756432,0.001603248,0.0009938953,0.002239278,0.0007397484,0.0003906964,0.005671021],"category_scores_gemma":[0.01887475,0.0002905747,0.0004938405,0.001890452,0.001361229,0.001112329,0.003430067,0.0008051858,0.0008467025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002123989,"about_ca_system_score_gemma":0.001986654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02557551,"about_ca_topic_score_gemma":0.05408263,"domain_scores_codex":[0.9911633,0.00530771,0.0002853838,0.0004292194,0.001270187,0.001544357],"domain_scores_gemma":[0.9789442,0.007161725,0.007794951,0.0009992421,0.00264355,0.002456295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005211129,0.0005819925,0.9492264,0.0002206182,0.0002781013,0.0002686123,0.001241903,0.002952663,0.0003518435,0.00163131,0.0033929,0.03933258],"study_design_scores_gemma":[0.0000113203,0.0003781484,0.9932134,0.00003773128,0.00004327898,0.00006891292,0.002599607,0.0006732669,0.0001859051,0.0001296957,0.002646322,0.00001239826],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904902,0.0003338638,0.0003179719,0.0005699056,0.00002573362,0.0000542277,0.0008338802,0.00002312264,0.007351128],"genre_scores_gemma":[0.9982464,0.0001361454,0.0001582616,0.00005227756,0.00001399102,0.00003098297,0.0003441346,0.000005761754,0.001011948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02557551,"threshold_uncertainty_score":0.05085331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1265163092256219,"score_gpt":0.4307391001005748,"score_spread":0.3042227908749529,"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."}}