{"id":"W2346538013","doi":"","title":"What is Near and Recent in Crime for a Homeowner? The Cases of Denver and Seattle","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Mile; Measure (data warehouse); Nonparametric statistics; Order (exchange); Demographic economics; Economics; Econometrics; Criminology; Geography; Psychology; Finance; Computer science; Archaeology","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":[0.0007874172,0.0002058633,0.0003826638,0.001678591,0.001619724,0.001394104,0.0008398284,0.0008589346,0.001755273],"category_scores_gemma":[0.006001448,0.0002215606,0.0002804916,0.001878928,0.002042818,0.001387528,0.001134692,0.001134655,0.0001595901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001515838,"about_ca_system_score_gemma":0.0004114502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1884563,"about_ca_topic_score_gemma":0.424783,"domain_scores_codex":[0.9987465,0.0004817765,0.00007380521,0.0002720929,0.0001596059,0.0002661668],"domain_scores_gemma":[0.9948621,0.001579515,0.00209345,0.0004150923,0.000445975,0.0006038913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001448758,0.000107747,0.9722146,0.00003462559,0.0001342355,0.002560661,0.006474838,0.0004968383,0.0002432135,0.002461933,0.003876111,0.01125038],"study_design_scores_gemma":[0.000006796115,0.00005046599,0.9630435,0.00009159221,0.00005267102,0.002286564,0.02814583,0.0008151008,0.000216296,0.0005212656,0.004745386,0.0000244685],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964509,0.0003448405,0.00008990274,0.0008103903,0.00001528426,0.000003807148,0.0001483889,0.000002307043,0.00213411],"genre_scores_gemma":[0.9990109,0.000240818,0.00008107738,0.00008017934,0.00002000175,0.000003236267,0.0001743797,0.000003844966,0.0003854486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1884563,"threshold_uncertainty_score":0.3747187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0659685960423705,"score_gpt":0.3041158917210482,"score_spread":0.2381472956786777,"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."}}