{"id":"W6979353124","doi":"","title":"Data-efficient rapid prediction of urban airflow and temperature fields for complex building geometries","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Canada First Research Excellence Fund","keywords":"Computational fluid dynamics; Wake; Wind speed; Speedup; Airflow; Training (meteorology); Generalization; Flow (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002698571,0.0006483532,0.0003427222,0.0002665084,0.0002083379,0.0003115679,0.0008908143,0.0006509725,0.001481107],"category_scores_gemma":[0.00112579,0.0003093362,0.0004744613,0.0002236839,0.0002964688,0.0006897081,0.0004933763,0.0008597932,0.000473631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000343077,"about_ca_system_score_gemma":0.0007825755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01095693,"about_ca_topic_score_gemma":0.01717295,"domain_scores_codex":[0.999941,0.000009089603,0.000002447962,0.00002293702,0.00001624509,0.000008292801],"domain_scores_gemma":[0.9997318,0.0001336531,0.00002297447,0.00004699799,0.00004398313,0.00002049281],"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":[0.00004411773,0.00007999605,0.002768698,0.00003332907,0.00001878832,0.00006256057,0.00003596436,0.9264922,0.006237721,0.0007924324,0.001138073,0.06229615],"study_design_scores_gemma":[0.00000163048,0.000003472259,0.0001338422,7.089615e-7,5.754594e-7,0.000003330239,0.000002470336,0.9992157,0.0003264434,0.0002442923,0.00006624104,0.000001144895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1675435,0.000146381,0.82579,0.0002641832,0.00006483925,0.00005911664,0.0004673274,0.003201827,0.002462913],"genre_scores_gemma":[0.8395907,0.00009693904,0.1576044,0.00008302032,0.00003183731,0.0001024958,0.0007959271,0.0001451946,0.001549422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01095693,"threshold_uncertainty_score":0.02178627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03949994277615668,"score_gpt":0.2615920428536215,"score_spread":0.2220921000774649,"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."}}