{"id":"W4297415292","doi":"","title":"A posteriori error estimation for a dual mixed finite element method for quasi–Newtonian flows whose viscosity obeys a power law or Carreau law","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Power-law fluid; Power law; Non-Newtonian fluid; Law; A priori and a posteriori; Mathematics; Newtonian fluid; Finite element method; Viscosity; Dual (grammatical number); Applied mathematics; Physics; Mechanics; Thermodynamics; Political science; Philosophy; Statistics","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":[0.002340441,0.0007346485,0.0008025798,0.001010593,0.0004020906,0.001404278,0.001213422,0.001758682,0.001080385],"category_scores_gemma":[0.005993605,0.0006111815,0.0007692599,0.0002646309,0.001287749,0.001081858,0.001623516,0.001575093,0.0003444494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006034801,"about_ca_system_score_gemma":0.001018276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001891415,"about_ca_topic_score_gemma":0.001126878,"domain_scores_codex":[0.9991758,0.0003181679,0.00004585733,0.0001040007,0.0003168655,0.00003924783],"domain_scores_gemma":[0.9975806,0.001278575,0.000266526,0.0002085594,0.0005364025,0.000129195],"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":[0.0006001079,0.0001561909,0.003302576,0.0004777012,0.0001605008,0.0001662635,0.0003077532,0.6760429,0.06023688,0.1614376,0.001155028,0.09595648],"study_design_scores_gemma":[0.000004935462,0.00001901545,0.0001053963,0.000008870041,0.000005137611,0.00001861383,0.000004909108,0.9934512,0.002392054,0.003518541,0.000463646,0.000007543328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01372568,0.0001111043,0.9852861,0.0001088581,0.00002527968,0.0000154292,0.00001721191,0.00006060765,0.000649776],"genre_scores_gemma":[0.281512,0.000159393,0.7147184,0.00007805013,0.00005074476,0.0001572594,0.000109772,0.0001336694,0.00308073],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002340441,"threshold_uncertainty_score":0.01237756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03982879251317178,"score_gpt":0.3351972401155806,"score_spread":0.2953684476024088,"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."}}