{"id":"W4205637599","doi":"10.1016/j.uclim.2021.101063","title":"CityFFD – City fast fluid dynamics for urban microclimate simulations on graphics processing units","year":2022,"lang":"en","type":"article","venue":"Urban Climate","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microclimate; Computational fluid dynamics; Computer science; Meteorology; Airflow; Environmental science; Benchmark (surveying); Large eddy simulation; Turbulence; Simulation; Engineering; Aerospace engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0008104252,0.001926261,0.001372466,0.0005953069,0.0009737015,0.001589865,0.003789639,0.001784523,0.03812102],"category_scores_gemma":[0.00319604,0.001116949,0.001566948,0.0009006007,0.0008020282,0.001615297,0.002189528,0.002564284,0.005740454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009604211,"about_ca_system_score_gemma":0.0018659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01747733,"about_ca_topic_score_gemma":0.01861259,"domain_scores_codex":[0.9994549,0.0001533549,0.00003427271,0.00008028179,0.0001829714,0.00009411814],"domain_scores_gemma":[0.9987563,0.0004510976,0.00004166195,0.0002330297,0.000368376,0.0001495664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006890448,0.0002674446,0.002807422,0.0004354887,0.0003689765,0.0002911811,0.0003956304,0.825881,0.006243742,0.01911733,0.085544,0.05795874],"study_design_scores_gemma":[0.0001666298,0.00002820823,0.000214819,0.00001481126,0.00001175865,0.00001938089,0.00001837313,0.9826355,0.002447467,0.002474833,0.01194076,0.00002736127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08982641,0.0004514169,0.7492087,0.001088324,0.001291198,0.0004823469,0.012924,0.09630905,0.04841851],"genre_scores_gemma":[0.4544613,0.0003648997,0.4779009,0.0006185422,0.0001644357,0.001314381,0.02099435,0.0212564,0.02292494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03812102,"threshold_uncertainty_score":0.1275275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316179334207779,"score_gpt":0.2452006438567413,"score_spread":0.2220388505146635,"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."}}