{"id":"W2333986242","doi":"10.2514/6.2014-0242","title":"Steady three-dimensional turbulent flow computations with a parallel Newton-Krylov-Schur algorithm","year":2014,"lang":"en","type":"article","venue":"52nd Aerospace Sciences Meeting","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computation; Computer science; Turbulence; Flow (mathematics); Algorithm; Applied mathematics; Mathematics; Mechanics; Geometry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000383408,0.0005765829,0.0006581728,0.0004199856,0.0008624574,0.0008341419,0.0009335895,0.0005396571,0.002231509],"category_scores_gemma":[0.000928249,0.0003463159,0.0005354806,0.00050743,0.0005696022,0.0006784339,0.0006747925,0.0004525131,0.0006967717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004514075,"about_ca_system_score_gemma":0.001487734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007077316,"about_ca_topic_score_gemma":0.00557797,"domain_scores_codex":[0.9998068,0.00003579607,0.000015218,0.00003057283,0.00008387952,0.00002771926],"domain_scores_gemma":[0.9996766,0.00008620305,0.00003053604,0.00005724662,0.0001237079,0.00002580666],"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":[0.0001664561,0.0001269479,0.001592436,0.00005301851,0.00003301335,0.0001109356,0.0001005766,0.936675,0.01333202,0.01274778,0.001322588,0.03373929],"study_design_scores_gemma":[0.00002319912,0.00003413151,0.000170443,0.000002167468,0.000004000701,0.00001712104,0.000006656993,0.9952858,0.002958239,0.0009883811,0.0005030472,0.000006840514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3018076,0.0001394054,0.668646,0.0002047616,0.00006589892,0.0001580752,0.0003521977,0.003743304,0.02488276],"genre_scores_gemma":[0.6345406,0.0001121292,0.3591752,0.00005085234,0.00002729872,0.000224656,0.0004723982,0.0002962923,0.005100444],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007077316,"threshold_uncertainty_score":0.01407224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008008814082157418,"score_gpt":0.2089535381236153,"score_spread":0.2009447240414579,"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."}}