{"id":"W4361268275","doi":"10.1007/s00267-023-01813-0","title":"Impact of COVID-19 Restrictions on the Urban Thermal Environment of Edmonton, Canada","year":2023,"lang":"en","type":"article","venue":"Environmental Management","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"General Electric (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Universities Space Research Association","keywords":"Geography; Socioeconomic status; Pandemic; Urban heat island; Land use; Census; Population; Equity (law); Coronavirus disease 2019 (COVID-19); Socioeconomics; Environmental health; Economics; Meteorology; Political science; Engineering; Civil engineering; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001082425,0.0003595583,0.0004441822,0.0006266485,0.004746224,0.002627832,0.001878315,0.001138275,0.007766692],"category_scores_gemma":[0.00231675,0.0003693249,0.0006504832,0.0006890397,0.001211771,0.0003660734,0.001478852,0.001618093,0.0004227127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05364846,"about_ca_system_score_gemma":0.1174151,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961541,"about_ca_topic_score_gemma":0.9988952,"domain_scores_codex":[0.9978703,0.0001601933,0.00003706892,0.0001381774,0.0006068502,0.001187408],"domain_scores_gemma":[0.9970078,0.0002349557,0.0001271627,0.00009866333,0.001300098,0.001231306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004188457,0.001321053,0.5557612,0.0007922839,0.0005847141,0.003486641,0.005523899,0.03435551,0.01079753,0.04547199,0.2384914,0.09922533],"study_design_scores_gemma":[0.0001803608,0.0001603097,0.8574674,0.0001886645,0.0001011682,0.00009530172,0.00483547,0.004646759,0.0014308,0.0005810915,0.130219,0.00009367954],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8462853,0.001419023,0.0005240584,0.01002822,0.0003579788,0.0002037132,0.005812748,0.0001443513,0.1352247],"genre_scores_gemma":[0.890276,0.0008438943,0.0007373635,0.002248306,0.00005682386,0.000119744,0.002737376,0.00005924862,0.1029213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05364846,"threshold_uncertainty_score":0.3892487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137311186036127,"score_gpt":0.212213343447712,"score_spread":0.2008402315873508,"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."}}