{"id":"W2299604037","doi":"10.4271/2016-01-1624","title":"A System for Simulating Road-Representative Atmospheric Turbulence for Ground Vehicles in a Large Wind Tunnel","year":2016,"lang":"en","type":"article","venue":"SAE International Journal of Passenger Cars - Mechanical Systems","topic":"Aerodynamics and Fluid Dynamics Research","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Transport Canada","keywords":"Turbulence; Wind tunnel; Atmospheric turbulence; Environmental science; Meteorology; Ground level; Marine engineering; Aerospace engineering; Engineering; Physics; Civil 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007439003,0.0003383553,0.0001876372,0.0002303727,0.0002786017,0.0003657924,0.0006326932,0.0003758825,0.004097611],"category_scores_gemma":[0.0007852359,0.000170367,0.0002826845,0.0001950916,0.0001895805,0.0002800208,0.0002951284,0.0003661026,0.0003932872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000433807,"about_ca_system_score_gemma":0.0008318579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006896983,"about_ca_topic_score_gemma":0.007955004,"domain_scores_codex":[0.9998735,0.00004176042,0.000009423028,0.00001625705,0.00004180708,0.00001713632],"domain_scores_gemma":[0.9996904,0.0001397831,0.00001816887,0.00003392563,0.00008115341,0.00003657689],"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":[0.0005619267,0.0004018118,0.006962351,0.00016884,0.00004444607,0.000216032,0.0002850127,0.8848216,0.07400431,0.002388172,0.003218758,0.02692666],"study_design_scores_gemma":[0.0001312255,0.0004322438,0.001732872,0.000008771493,0.00001056955,0.00002117147,0.00005366109,0.9836494,0.01087783,0.0002471364,0.002815227,0.00001992444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6942174,0.00004158344,0.2842292,0.0001482488,0.0001052781,0.001352554,0.002473805,0.006273119,0.01115869],"genre_scores_gemma":[0.9184166,0.00003868136,0.07656822,0.00002618405,0.000005734243,0.000632422,0.001137863,0.0001734744,0.003000836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006896983,"threshold_uncertainty_score":0.01371366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01711345197976024,"score_gpt":0.2890935803623889,"score_spread":0.2719801283826286,"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."}}