{"id":"W1972914682","doi":"10.1115/imece2009-10569","title":"An Aerodynamic Study and Design Methodology for the 2009 Supermileage Body","year":2009,"lang":"en","type":"article","venue":"","topic":"Aerodynamics and Fluid Dynamics Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"University of Windsor","keywords":"Computational fluid dynamics; Aerodynamics; Drag coefficient; Aerodynamic drag; Computer science; Airfoil; Aerospace engineering; Drag; Lift-to-drag ratio; Lift coefficient; Marine engineering; Automotive engineering; Simulation; Engineering; Turbulence; Physics; Mechanics","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":[0.001393016,0.0001692527,0.0002091449,0.00008510501,0.0001631241,0.00008278481,0.0003038206,0.0000816353,0.00002523508],"category_scores_gemma":[0.00005528046,0.0001172336,0.00003955598,0.0001410325,0.00005229223,0.0001098337,0.000023034,0.0001855033,0.000004336123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003275069,"about_ca_system_score_gemma":0.00001439545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003612827,"about_ca_topic_score_gemma":0.0002865471,"domain_scores_codex":[0.9988818,0.0001615288,0.0001974553,0.0002506697,0.0001316705,0.0003769195],"domain_scores_gemma":[0.9988329,0.0006077854,0.00000982247,0.000400834,0.00005128919,0.00009733601],"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":[0.0003520316,0.000950608,0.002078482,0.00006353838,0.0005222582,0.0000512339,0.002847723,0.318167,0.4239598,0.04195394,0.002621508,0.2064319],"study_design_scores_gemma":[0.0004274063,0.0007267356,0.04631543,0.000001158682,0.00002426549,0.00000706665,0.0004229979,0.9503667,0.00004738812,0.001454042,0.00005447396,0.0001523068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3505555,0.0002631774,0.6474823,0.0001426576,0.00008792199,0.001020707,0.00001062663,0.0001529679,0.0002841025],"genre_scores_gemma":[0.9773546,0.0001634503,0.02200281,0.00008029921,0.00005166107,0.00006329087,0.000008237983,0.00003087478,0.0002447578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6321997,"threshold_uncertainty_score":0.4780646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06423130882247508,"score_gpt":0.3417633922465099,"score_spread":0.2775320834240348,"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."}}