{"id":"W2032794421","doi":"10.2514/6.2010-4678","title":"Improvements in Accuracy and Efficiency for a Far-Field Drag Prediction and Decomposition Method","year":2010,"lang":"en","type":"article","venue":"28th AIAA Applied Aerodynamics Conference","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Polytechnique Montréal","funders":"Fondation J. Armand Bombardier; Polytechnique Montréal; Pratt and Whitney Canada","keywords":"Drag; Computer science; Field (mathematics); Decomposition; Aerospace engineering; Mathematics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001310339,0.0008895039,0.0007462497,0.0007636597,0.0003931799,0.001131543,0.001090078,0.0009883337,0.003480889],"category_scores_gemma":[0.003302218,0.0003908143,0.0008957125,0.0004090405,0.0005191113,0.001165589,0.00150311,0.001570195,0.001900847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003391524,"about_ca_system_score_gemma":0.0005555223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00169015,"about_ca_topic_score_gemma":0.001105914,"domain_scores_codex":[0.9989066,0.0002537922,0.00006250615,0.0001247052,0.0005673374,0.00008508046],"domain_scores_gemma":[0.9984515,0.0004698899,0.00007117925,0.0003928911,0.0005365761,0.00007802227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000623582,0.0002957185,0.002546347,0.000314845,0.00008689789,0.0002723149,0.000269787,0.323704,0.1332192,0.06719823,0.005440662,0.4660283],"study_design_scores_gemma":[0.00002579909,0.00005380163,0.0004717752,0.00002639758,0.000009379991,0.0000769029,0.00001463191,0.9811926,0.01182507,0.002786909,0.003490295,0.00002650815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02490469,0.0004745726,0.9675426,0.0002019722,0.0001584673,0.00003679557,0.00007110668,0.001159695,0.005450152],"genre_scores_gemma":[0.2482959,0.000462009,0.7432416,0.000120521,0.0001150867,0.00006814217,0.0002799696,0.0004763582,0.006940496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003480889,"threshold_uncertainty_score":0.01164472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005332008170474752,"score_gpt":0.2394668575335169,"score_spread":0.2341348493630421,"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."}}