{"id":"W1828718921","doi":"10.1186/s40163-015-0039-0","title":"Daily crime flows within a city","year":2015,"lang":"en","type":"article","venue":"Crime Science","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"TRIPS architecture; Geography; Recreation; Census; Distribution (mathematics); Agency (philosophy); Population; Economic geography; Socioeconomics; Demographic economics; Criminology; Demography; Sociology; Political science; Economics; Transport engineering","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":[0.0003076383,0.0002263413,0.0004052837,0.003854104,0.0008735795,0.002406307,0.0004528312,0.0004377536,0.009727199],"category_scores_gemma":[0.002606967,0.0002768243,0.00051858,0.005394639,0.0004379853,0.001623718,0.001774864,0.0006088545,0.001871939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001353668,"about_ca_system_score_gemma":0.0007838995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05719981,"about_ca_topic_score_gemma":0.07848037,"domain_scores_codex":[0.9992164,0.0002444917,0.00008122075,0.0001582028,0.0001694427,0.0001300629],"domain_scores_gemma":[0.998136,0.0004610925,0.000579197,0.0001059462,0.0003537869,0.0003639101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001680146,0.000176292,0.9223685,0.0002493798,0.0004477912,0.0002962681,0.006887498,0.00556608,0.0002714517,0.007004763,0.02368309,0.03288094],"study_design_scores_gemma":[0.000005935986,0.00005187791,0.9761868,0.00006499723,0.00004182213,0.0001735845,0.007887181,0.00386065,0.00007960126,0.00117929,0.010425,0.00004337205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652275,0.0004336051,0.0009669553,0.0006156629,0.00004383296,0.00006288465,0.01896184,0.000113839,0.01357385],"genre_scores_gemma":[0.9871998,0.0005938752,0.0007740594,0.00004148308,0.00004082203,0.00007408875,0.007350753,0.00002933553,0.003895622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05719981,"threshold_uncertainty_score":0.1137337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1710772560989031,"score_gpt":0.4162244415848324,"score_spread":0.2451471854859293,"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."}}