{"id":"W2299695489","doi":"10.4271/2016-01-1613","title":"Evaluation of the Aerodynamics of Drag Reduction Technologies for Light-duty Vehicles: a Comprehensive Wind Tunnel Study","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":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada; National Research Council Canada","funders":"U.S. Environmental Protection Agency","keywords":"Drag; Aerodynamics; Wind tunnel; Marine engineering; Reduction (mathematics); Aerodynamic drag; Aerospace engineering; Heavy duty; Environmental science; Automotive engineering; Engineering; Aeronautics; Meteorology; Physics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.001754232,0.0001575765,0.0003860553,0.0002364825,0.00003798172,0.00003054386,0.0007227701,0.0001524266,0.000002760243],"category_scores_gemma":[0.0003905769,0.00009654758,0.0002484345,0.0001915788,0.00007285471,0.0001597886,0.0001147117,0.0002245917,7.498022e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004667351,"about_ca_system_score_gemma":0.0001265575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001833895,"about_ca_topic_score_gemma":0.00006993437,"domain_scores_codex":[0.996721,0.0002226418,0.0009638891,0.0001600483,0.001753396,0.0001789948],"domain_scores_gemma":[0.9959446,0.0002302036,0.000489415,0.0002794386,0.003013032,0.00004327091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008218981,0.0002328595,0.0003229404,0.00005547891,0.001015243,0.000003090969,0.000227159,0.02239731,0.9637431,0.003193557,0.0001200481,0.00860703],"study_design_scores_gemma":[0.01290256,0.001790027,0.04107913,0.002473513,0.001103804,0.000412558,0.01675447,0.8781548,0.03058119,0.01336446,0.0006402166,0.0007433369],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894065,0.0004206813,0.0058711,0.0004501201,0.002933118,0.0007703159,0.00008756511,0.00002639064,0.00003419126],"genre_scores_gemma":[0.999508,0.00009787393,0.0001515575,0.000001248688,0.0001679428,0.0000244906,0.000002216397,0.00002753975,0.00001910581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9331619,"threshold_uncertainty_score":0.3937096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204788419316964,"score_gpt":0.2989854243086691,"score_spread":0.2669375401154995,"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."}}