{"id":"W1999304592","doi":"10.1007/s10109-012-0164-1","title":"Exploring links between juvenile offenders and social disorganization at a large map scale: a Bayesian spatial modeling approach","year":2012,"lang":"en","type":"article","venue":"Journal of Geographical Systems","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geography; Recidivism; Context (archaeology); Census; Scale (ratio); Population; Criminology; Ethnic group; Psychology; Demography; Cartography; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001676594,0.00011206,0.0003165424,0.0001981815,0.0007547218,0.0001333256,0.0001509579,0.0001989993,0.00006146566],"category_scores_gemma":[0.00003769618,0.00009893552,0.0002230761,0.0002526829,0.00008906554,0.0005804837,0.00006793937,0.0003771698,0.000003256253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008694664,"about_ca_system_score_gemma":0.00002384199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001363868,"about_ca_topic_score_gemma":0.0002746549,"domain_scores_codex":[0.9980631,0.0003179537,0.0005721709,0.0001221499,0.0005270752,0.0003975753],"domain_scores_gemma":[0.9991882,0.0000441758,0.0003040977,0.00006405849,0.0001527594,0.0002466516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002267781,0.0002688042,0.9752858,0.0001497646,0.0001403199,0.000001252094,0.02060283,0.00007891803,0.0000549225,0.00158258,0.0003958174,0.001416376],"study_design_scores_gemma":[0.007880199,0.00104957,0.6046389,0.001671312,0.001835924,0.000154907,0.221273,0.06637049,0.00007390751,0.001207405,0.09118772,0.002656759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8125092,0.0005491208,0.1848398,0.0007292924,0.0008127437,0.0001656658,0.0000158748,0.00002288345,0.0003553514],"genre_scores_gemma":[0.9970512,0.0000588627,0.0001084004,0.00001502688,0.00269048,0.000007606218,0.000008554401,0.00001619926,0.00004368477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3706469,"threshold_uncertainty_score":0.5804786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1098906349080957,"score_gpt":0.3072820509984176,"score_spread":0.1973914160903219,"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."}}