{"id":"W2953953307","doi":"10.1016/j.cam.2019.05.006","title":"A priori and a posteriori estimates of stabilized mixed finite volume methods for the incompressible flow arising in arteriosclerosis","year":2019,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Science Foundation","keywords":"Mathematics; Finite element method; Finite volume method; Variational inequality; Applied mathematics; A priori and a posteriori; Boundary value problem; Convergence (economics); Compressibility; Mathematical analysis; Incompressible flow; Flow (mathematics); Mixed finite element method; Geometry; Mechanics","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":[0.003648822,0.001688047,0.0009380681,0.002226548,0.0006309571,0.001985786,0.001494426,0.002197252,0.002012955],"category_scores_gemma":[0.0127871,0.0008092152,0.0008764009,0.0004015367,0.002298169,0.002032719,0.003077679,0.002310238,0.0002574808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001018004,"about_ca_system_score_gemma":0.001152903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002121003,"about_ca_topic_score_gemma":0.001954264,"domain_scores_codex":[0.9992394,0.0004562936,0.00003459033,0.00007399121,0.0001537465,0.00004192721],"domain_scores_gemma":[0.9905677,0.006282251,0.0007719041,0.0002970494,0.001601898,0.0004790686],"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":[0.001249883,0.000360595,0.005035309,0.0008503333,0.0002919721,0.0003551312,0.0005948896,0.583186,0.05772372,0.2914108,0.002847297,0.05609398],"study_design_scores_gemma":[0.000007018994,0.00005692821,0.0003553991,0.00002920007,0.00001394268,0.00002573292,0.00002134643,0.9861552,0.002287555,0.01066448,0.0003644307,0.00001880461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1366673,0.001580157,0.8561743,0.0008243882,0.0002561845,0.0000649632,0.0001028059,0.0002485802,0.004081335],"genre_scores_gemma":[0.7760699,0.001152735,0.210001,0.0002645417,0.0004109071,0.0002561818,0.0003778152,0.000413008,0.01105384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003648822,"threshold_uncertainty_score":0.019297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02201611201152736,"score_gpt":0.3125806112638145,"score_spread":0.2905644992522871,"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."}}