{"id":"W2052532943","doi":"10.1559/152304010790588089","title":"The Role of Maps in Neighborhood-level Heat Vulnerability Assessment for the City of Toronto","year":2010,"lang":"en","type":"article","venue":"Cartography and Geographic Information Science","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health; Simon Fraser University; Toronto Metropolitan University","funders":"","keywords":"Vulnerability (computing); Urban heat island; Geography; Hazard; Vulnerability assessment; Natural hazard; Extreme weather; Cartography; Population; Climate change; Environmental resource management; Psychological intervention; Environmental planning; Computer science; Environmental science; Environmental health; Meteorology; Computer security; Medicine","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":[0.0009639574,0.0002718595,0.0001607863,0.002140133,0.0009180799,0.002080626,0.0002587149,0.0001745923,0.002534398],"category_scores_gemma":[0.008238322,0.0001181343,0.0002078722,0.00266507,0.0004136543,0.0005994113,0.0008160271,0.000134051,0.0001397204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00435927,"about_ca_system_score_gemma":0.0035738,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5561957,"about_ca_topic_score_gemma":0.6943197,"domain_scores_codex":[0.9994252,0.0003111503,0.00002327249,0.00002907877,0.0001655299,0.00004589769],"domain_scores_gemma":[0.997573,0.001249033,0.0001586273,0.0001272863,0.0007186683,0.0001734706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006529783,0.00008064135,0.5251133,0.0006657812,0.0002114291,0.0006710922,0.01317918,0.1839589,0.002909586,0.01576301,0.01035751,0.2464365],"study_design_scores_gemma":[0.00002263648,0.0001313503,0.6272561,0.0002449173,0.0001586884,0.0001579221,0.01793349,0.3306151,0.002168512,0.005689991,0.01550643,0.0001148157],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964047,0.0004401779,0.01319193,0.0005442734,0.00002222959,0.0002223197,0.00276222,0.0002373135,0.01853254],"genre_scores_gemma":[0.9898212,0.0001659405,0.008784881,0.000004372391,0.000002996695,0.00004143609,0.000395265,0.00001283447,0.0007710598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4438043,"threshold_uncertainty_score":0.892836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974583967206975,"score_gpt":0.2997189477365385,"score_spread":0.2799731080644687,"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."}}