{"id":"W2443275185","doi":"10.1097/01.ede.0000276628.94631.dd","title":"Use of GIS to Direct Public Health Interventions for Heat-Related Illness","year":2007,"lang":"en","type":"article","venue":"Epidemiology","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Geospatial analysis; Psychological intervention; Public health; Recreation; Socioeconomic status; Heat illness; Geographic information system; Geography; Environmental health; Location; Public health interventions; Medicine; Environmental planning; Cartography; Population; Nursing; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003802933,0.0009952333,0.0005107107,0.005029838,0.0005731616,0.0023761,0.0007306443,0.0003519912,0.01332581],"category_scores_gemma":[0.01893253,0.0005186551,0.0008950292,0.005051157,0.0004794617,0.001578179,0.001886358,0.000486889,0.001476583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002214974,"about_ca_system_score_gemma":0.003708745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08933064,"about_ca_topic_score_gemma":0.1149257,"domain_scores_codex":[0.9970881,0.002016829,0.0001920764,0.0002206929,0.0003956522,0.00008656706],"domain_scores_gemma":[0.9883298,0.007866053,0.0008772179,0.0009865032,0.001722531,0.0002178677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000667342,0.0005542815,0.1651782,0.003158954,0.0009747776,0.000451737,0.01040067,0.05570409,0.002403691,0.01463871,0.06986848,0.675999],"study_design_scores_gemma":[0.000856678,0.00110576,0.2871967,0.002994618,0.001118015,0.0005055587,0.02582291,0.3063402,0.007836574,0.0336673,0.3320291,0.0005265832],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3206095,0.003671349,0.3565052,0.01000433,0.0008793463,0.005484788,0.1074708,0.02957016,0.1658044],"genre_scores_gemma":[0.5702729,0.002178151,0.4041942,0.0003301252,0.00008910853,0.002106883,0.01358698,0.0005246237,0.006717025],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08933064,"threshold_uncertainty_score":0.1776214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4156409536220874,"score_gpt":0.4650285727711638,"score_spread":0.04938761914907636,"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."}}