{"id":"W1967781207","doi":"10.1504/ijesms.2013.052376","title":"Numerical simulation and wind tunnel measurements on a tricycle wheel sub-system","year":2013,"lang":"en","type":"article","venue":"International Journal of Engineering Systems Modelling and Simulation","topic":"Aerodynamics and Fluid Dynamics Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drag; Wind tunnel; Drag coefficient; Aerodynamics; Turbulence; Fender; Aerodynamic drag; Computational fluid dynamics; Parasitic drag; Reduction (mathematics); Computer simulation; Suspension (topology); Numerical analysis; Engineering; Simulation; Aerospace engineering; Mechanics; Mechanical engineering; Physics; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003126825,0.0001439405,0.0001983853,0.0003126449,0.00003752079,0.0001875932,0.0001027242,0.00008323251,0.00000121429],"category_scores_gemma":[0.0000367289,0.0001356793,0.00004531341,0.00007961541,0.000009004755,0.0003000096,0.00001225656,0.0001890321,0.000003790547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001903027,"about_ca_system_score_gemma":0.000009646577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002774522,"about_ca_topic_score_gemma":2.803737e-7,"domain_scores_codex":[0.9987232,0.00002256754,0.0004664208,0.0001154061,0.0005250313,0.0001473507],"domain_scores_gemma":[0.999149,0.0001626201,0.00009334432,0.00007162885,0.0004145173,0.0001088612],"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":[0.00001646043,0.00001187887,0.0002742228,0.00005993677,0.00009246071,0.000003818375,0.00009844894,0.996323,0.002000342,0.0001520453,0.000003324179,0.0009640922],"study_design_scores_gemma":[0.000443661,0.000037093,0.002013038,0.0002236408,0.000009344819,0.00001797168,0.00002500947,0.9970339,0.00001961364,0.00002453239,0.00003192376,0.0001202556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5705193,0.0002281896,0.4286313,0.0000115992,0.0004399595,0.00009681364,0.000002340854,0.00003225148,0.00003824385],"genre_scores_gemma":[0.9991437,0.00003959907,0.0005198939,0.000002663253,0.0002456215,0.000003209548,0.000004183567,0.00003088673,0.00001021814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4286244,"threshold_uncertainty_score":0.5532842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03058689592898784,"score_gpt":0.2568192367258823,"score_spread":0.2262323407968945,"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."}}