{"id":"W2185463413","doi":"","title":"L 1 -ERROR ESTIMATES AND SUPERCONVERGENCE IN MAXIMUM NORM OF MIXED FINITE ELEMENT METHODS FOR NONFICKIAN FLOWS IN POROUS MEDIA","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Superconvergence; Mathematics; Estimator; Finite element method; Gauss; Applied mathematics; Porous medium; A priori and a posteriori; Interpolation (computer graphics); Norm (philosophy); Mathematical analysis; Element (criminal law); Porosity; Computer science; Physics; 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":[0.004476561,0.0009744611,0.0006556098,0.001335419,0.0004311432,0.001315637,0.0009107283,0.001167377,0.001403945],"category_scores_gemma":[0.01529365,0.0004047409,0.000614207,0.0004140678,0.002286537,0.001803616,0.001718135,0.001744794,0.0002824482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006509797,"about_ca_system_score_gemma":0.0006897413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001255983,"about_ca_topic_score_gemma":0.001059453,"domain_scores_codex":[0.9988775,0.0005792653,0.00005298667,0.00007550542,0.0003708583,0.00004393646],"domain_scores_gemma":[0.9946148,0.003729542,0.0003925016,0.0002268014,0.0009125608,0.0001237512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003449135,0.0001397124,0.002449645,0.0006771154,0.00008949442,0.0001739869,0.0006499558,0.42941,0.01595881,0.4751473,0.001946949,0.07301201],"study_design_scores_gemma":[0.000005053203,0.00002900022,0.0001673289,0.00002490965,0.000005562267,0.00002674965,0.00001955358,0.9751129,0.003072705,0.02089392,0.000631736,0.00001052545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04389582,0.0006637104,0.9514433,0.0002552306,0.00005893261,0.00003361666,0.00003303343,0.00008753109,0.003528945],"genre_scores_gemma":[0.5849502,0.0009006018,0.4069858,0.0001456828,0.0001024044,0.0002718488,0.0001993033,0.000228681,0.006215539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004476561,"threshold_uncertainty_score":0.02367461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03922090975904106,"score_gpt":0.3586752453787804,"score_spread":0.3194543356197393,"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."}}