{"id":"W4386574369","doi":"10.1016/j.scs.2023.104925","title":"Thermal effects of cool roofs and urban vegetation during extreme heat events in three Canadian regions","year":2023,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; National Research Council Canada","funders":"","keywords":"Vegetation (pathology); Environmental science; Urban heat island; Wind speed; Relative humidity; Urban climate; Meteorology; Climatology; Microclimate; Climate change; Population; Air temperature; Climate model; Humidity; Urban climatology; Geography; Atmospheric sciences; Urban planning; Civil engineering; Geology; Engineering","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":[0.0002862216,0.0004062182,0.0004654129,0.0008745743,0.005835533,0.001556222,0.00113993,0.0006239447,0.001878926],"category_scores_gemma":[0.0006149447,0.0003179941,0.0005211097,0.002092978,0.001262906,0.0003273523,0.001050274,0.000725622,0.0001538021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02817809,"about_ca_system_score_gemma":0.01812122,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996627,"about_ca_topic_score_gemma":0.9992074,"domain_scores_codex":[0.9995663,0.00003163462,0.000008146927,0.00005469794,0.00008963881,0.0002497146],"domain_scores_gemma":[0.9993999,0.00004639545,0.00004680582,0.00001232946,0.0003028423,0.0001917054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001655374,0.0003759201,0.9372229,0.0001852856,0.0002692785,0.0006426972,0.02324023,0.003297066,0.009850461,0.0008276998,0.004581462,0.01785162],"study_design_scores_gemma":[0.000004845667,0.00001711853,0.9906278,0.000009569784,0.00001649283,0.00001787167,0.007664715,0.0002842726,0.0001638761,0.00002143028,0.001156573,0.00001549419],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967975,0.0001058569,0.0000483315,0.0000964129,0.000006971125,0.00001857361,0.0007327457,0.000004724322,0.002188964],"genre_scores_gemma":[0.9979297,0.0001038784,0.00009881373,0.00004016686,0.000003332038,0.00001537679,0.0005184208,0.000003729899,0.001286733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02817809,"threshold_uncertainty_score":0.2044473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006314638827592364,"score_gpt":0.1818620354176387,"score_spread":0.1755473965900463,"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."}}