{"id":"W3127859197","doi":"10.3389/fbuil.2021.603836","title":"Run-Time and Statistical Pedestrian Level Wind Map for Downtown Toronto","year":2021,"lang":"en","type":"article","venue":"Frontiers in Built Environment","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Toronto Metropolitan University","funders":"University of Toronto","keywords":"Downtown; Pedestrian; Wind speed; Computational fluid dynamics; Meteorology; Urbanization; Wind direction; Environmental science; Population; Visualization; Geography; Civil engineering; Engineering; Aerospace engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001849713,0.0002109048,0.0002893484,0.00001364884,0.0001497673,0.0000311389,0.0001381701,0.00008504076,0.003384145],"category_scores_gemma":[0.00003389106,0.0002038782,0.00005031374,0.00003438594,0.000275663,0.0001283439,0.0003006222,0.00008710266,0.0001158143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000460324,"about_ca_system_score_gemma":0.00001080385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003813363,"about_ca_topic_score_gemma":0.0003258863,"domain_scores_codex":[0.9984581,0.00004892623,0.0002572662,0.0005474438,0.0002660129,0.0004222684],"domain_scores_gemma":[0.999496,0.00005714536,0.0000449725,0.0002575118,0.000001709094,0.0001426621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002136747,0.0007781935,0.4157155,0.0001029569,0.0001794579,0.0001479622,0.002129852,0.00170029,0.007853454,0.0002742629,0.3676852,0.2032193],"study_design_scores_gemma":[0.002025982,0.0001962956,0.626739,0.00002885982,0.00006428197,0.000008140129,0.0009439758,0.00213553,0.001002143,0.002868791,0.3633572,0.0006297909],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8106808,0.01401182,0.1403714,0.008588548,0.002743353,0.002857621,0.001741023,0.0001274065,0.01887809],"genre_scores_gemma":[0.4843298,0.002363725,0.4803833,0.001016075,0.0004230652,0.0001998184,0.0002557735,0.0001071332,0.03092126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.340012,"threshold_uncertainty_score":0.9975269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131127577286101,"score_gpt":0.2217725716300455,"score_spread":0.2086598139014355,"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."}}