{"id":"W2331914037","doi":"10.2514/6.2013-1000","title":"A Polynomial Adaptive LCP Scheme for Viscous Compressible Flows","year":2013,"lang":"en","type":"article","venue":"51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Scheme (mathematics); Polynomial; Compressibility; Computer science; Applied mathematics; Mathematical optimization; Mathematics; Mechanics; Mathematical analysis; 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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0004579566,0.0003841797,0.0003207297,0.0001304641,0.001744351,0.0006571359,0.0004529337,0.0001293437,0.00001039049],"category_scores_gemma":[0.0001026654,0.0003142161,0.0001368671,0.0005305489,0.0002779441,0.000669984,0.0002537696,0.0002544633,0.0000260169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001502649,"about_ca_system_score_gemma":0.00009640263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003625829,"about_ca_topic_score_gemma":0.0004783706,"domain_scores_codex":[0.9978759,0.00004811713,0.0003579264,0.0005176826,0.0004153446,0.0007849779],"domain_scores_gemma":[0.9986784,0.0006130572,0.0001349339,0.0002427408,0.0001144385,0.0002163695],"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":[0.00009832311,0.0001041603,0.002397382,0.0001245683,0.0001723012,0.000002283292,0.001918494,0.4154763,0.4733244,0.01375362,0.08494063,0.007687564],"study_design_scores_gemma":[0.0006781896,0.0003924636,0.0003331395,0.0002263503,0.00002841866,0.00001612445,0.001738291,0.9919979,0.001533025,0.001437745,0.001138758,0.000479624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8654209,0.0009629761,0.1206805,0.007715612,0.001213378,0.001282537,0.00005626657,0.0004838236,0.002184063],"genre_scores_gemma":[0.9515109,0.0001165953,0.04736976,0.0001485848,0.0003593424,0.0001230125,0.00002642691,0.00005429318,0.0002910872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5765216,"threshold_uncertainty_score":0.999931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588558740525265,"score_gpt":0.2400658916721364,"score_spread":0.2241803042668838,"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."}}