{"id":"W4383497909","doi":"10.1016/j.buildenv.2023.110564","title":"Heat exposure variations and mitigation in a densely populated neighborhood during a hot day: Towards a people-oriented approach to urban climate management","year":2023,"lang":"en","type":"article","venue":"Building and Environment","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Environmental science; Urbanization; Climate change; Pedestrian; Urban climate; Adaptation (eye); Urban heat island; Extreme heat; Heat stress; Temporal scales; Environmental resource management; Meteorology; Thermal comfort; Computer science; Climatology; Geography; Atmospheric sciences; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003179686,0.0001849244,0.0001658457,0.0001468076,0.0002179734,0.00004570271,0.00007217385,0.00006900691,0.00003910892],"category_scores_gemma":[0.00001115001,0.0001894229,0.00002526695,0.0004172115,0.00003695268,0.0001499015,0.0002933373,0.00009184693,0.00004657294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002424007,"about_ca_system_score_gemma":0.000002185044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002050081,"about_ca_topic_score_gemma":0.00003287029,"domain_scores_codex":[0.9984493,0.00006616197,0.0002633376,0.0005431346,0.0002815419,0.0003965536],"domain_scores_gemma":[0.9995951,0.00001686929,0.00002717452,0.0002033171,0.000001460141,0.000156069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006995635,0.000252332,0.9365672,0.0001224394,0.000045515,0.00002658237,0.009873995,0.02140065,0.02293914,0.00130386,0.0003304509,0.007067848],"study_design_scores_gemma":[0.0007473158,0.00005394504,0.9808466,0.00004506783,0.00002909335,0.0000109597,0.0003399036,0.01690534,0.0003718603,0.0001351263,0.0002936417,0.0002211628],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961024,0.00004444379,0.002176693,0.0002844573,0.00004881812,0.0006082982,0.00001488005,0.00008395615,0.0006360736],"genre_scores_gemma":[0.996146,0.0002709918,0.003076577,0.00005912912,0.00002016627,0.0001977456,0.00005705736,0.0000229189,0.0001494646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04427936,"threshold_uncertainty_score":0.7724442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006818540871842454,"score_gpt":0.195842884516108,"score_spread":0.1890243436442655,"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."}}