{"id":"W2610060618","doi":"10.1016/j.apgeog.2017.08.005","title":"Socioeconomic characteristics and crash injury exposure: A case study in Florida using two-step floating catchment area method","year":2017,"lang":"en","type":"article","venue":"Applied Geography","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"U.S. Navy; University of North Florida; Institute of Aging; U.S. Department of Transportation; Center for Produce Safety; National Stroke Foundation; University of Florida; United States-Japan Foundation; Florida State University","keywords":"Crash; Catchment area; Drainage basin; Environmental science; Hydrology (agriculture); Geography; Forensic engineering; Geology; Engineering; Computer science; Cartography; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0008654547,0.0005479577,0.000378172,0.001712456,0.001843008,0.0006926711,0.0007215542,0.0008540741,0.001687516],"category_scores_gemma":[0.002398298,0.0003484004,0.0008869586,0.00186841,0.0005296208,0.0007852396,0.001026574,0.0006584225,0.0001533093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001660636,"about_ca_system_score_gemma":0.001109431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.194775,"about_ca_topic_score_gemma":0.2792882,"domain_scores_codex":[0.9992361,0.0003600831,0.00003287713,0.000126616,0.00007981097,0.0001644623],"domain_scores_gemma":[0.9991636,0.0002894955,0.000185381,0.00006616524,0.0001650632,0.0001302536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001547484,0.0008356051,0.9897893,0.00002143838,0.0001223722,0.001668295,0.001999329,0.0002811961,0.0004343744,0.0001424429,0.0001892572,0.004361586],"study_design_scores_gemma":[0.00001963006,0.0006388698,0.9814137,0.00002423617,0.0001885943,0.001225698,0.01235172,0.003398863,0.0002295658,0.000130762,0.0003415136,0.0000368732],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996265,0.00001979318,0.0001239094,0.00002257504,8.379787e-7,0.00001690694,0.00005450996,7.353391e-7,0.0001341418],"genre_scores_gemma":[0.9994592,0.00004671063,0.0002723896,0.000009389975,0.000001824915,0.0000166965,0.00007610143,7.214496e-7,0.0001169605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.194775,"threshold_uncertainty_score":0.3872825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491927558660726,"score_gpt":0.2711421733725324,"score_spread":0.2562228977859252,"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."}}