{"id":"W2322912868","doi":"10.2514/6.2003-71","title":"A Newton-Krylov Algorithm for Turbulent Aerodynamic Flows","year":2003,"lang":"en","type":"article","venue":"41st Aerospace Sciences Meeting and Exhibit","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Aerodynamics; Turbulence; Computer science; Computational fluid dynamics; Mechanics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006395648,0.0002292495,0.0002113791,0.00009485146,0.0004072474,0.0002053783,0.0001619737,0.00007437749,0.000007396432],"category_scores_gemma":[0.00005384985,0.0002184459,0.0000813809,0.0003572055,0.0001199822,0.0001437442,0.00002943661,0.0001185471,0.000009097534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000623763,"about_ca_system_score_gemma":0.00005318714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002710216,"about_ca_topic_score_gemma":0.00008275836,"domain_scores_codex":[0.9985827,0.00002046083,0.0002396635,0.0004087349,0.0002640894,0.0004843211],"domain_scores_gemma":[0.9994516,0.0001686733,0.00004101723,0.00013639,0.00006634944,0.0001359679],"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":[0.000006392308,0.00009327464,0.001917062,0.0001628645,0.00006816859,0.00001093601,0.0007135015,0.8938864,0.0157228,0.0347373,0.00148499,0.05119625],"study_design_scores_gemma":[0.0002627794,0.00005557868,0.0003437652,0.00005347321,0.00001249098,0.0000306494,0.0001441832,0.9950157,0.0001169043,0.001315903,0.002350864,0.0002976923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7990278,0.001176335,0.1935158,0.0003681933,0.0008451413,0.0003531619,0.0000257518,0.0002897993,0.004398011],"genre_scores_gemma":[0.8836481,0.0001919377,0.1154011,0.00007905314,0.0001173381,0.00003853937,0.00001746013,0.000044313,0.0004621175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1011293,"threshold_uncertainty_score":0.8907967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213327392738127,"score_gpt":0.2205977382769048,"score_spread":0.2084644643495235,"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."}}