{"id":"W3137409987","doi":"10.1002/nla.2426","title":"Low‐order preconditioning of the Stokes equations","year":2021,"lang":"en","type":"preprint","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Nuclear Security Administration; Office of Science; Advanced Scientific Computing Research; Sandia National Laboratories; U.S. Department of Energy","keywords":"Multigrid method; Discretization; Preconditioner; Order (exchange); Mathematics; Stokes flow; Mathematical analysis; Geometry; Partial differential equation; Linear system; Flow (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001036692,0.0003055806,0.0004446345,0.00007051309,0.0001500026,0.00004260005,0.0005273615,0.0001833462,0.0001129784],"category_scores_gemma":[0.0002701079,0.0002408215,0.0001537645,0.000924787,0.0001834417,0.00007490058,0.0002856235,0.0008154616,0.00001901379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009392322,"about_ca_system_score_gemma":0.0001926572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003206258,"about_ca_topic_score_gemma":0.000001840417,"domain_scores_codex":[0.9983063,0.00008221604,0.0005950134,0.0003694411,0.0004168676,0.0002301707],"domain_scores_gemma":[0.9973488,0.0009936804,0.0002702742,0.0008779111,0.0004115508,0.00009779782],"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":[0.0000019925,0.000119515,0.00003917027,0.0003664812,0.0001192698,2.569141e-7,0.0001505177,0.9837541,0.0001394971,0.008339353,0.00004064232,0.00692923],"study_design_scores_gemma":[0.0002924215,0.00003685779,0.00106849,0.0005572346,0.0002511047,0.00001366186,0.0002001965,0.9219814,0.007207948,0.06601663,0.001610795,0.0007632544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00242026,0.0002520455,0.9945396,0.0002248874,0.0001828777,0.0008951841,0.0001125146,0.0002781987,0.001094426],"genre_scores_gemma":[0.2927097,0.00002105574,0.7055672,0.00007674762,0.0001592907,0.001183724,0.0001521008,0.00008345655,0.00004674133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2902894,"threshold_uncertainty_score":0.9820417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01827425167728905,"score_gpt":0.2851458680345385,"score_spread":0.2668716163572494,"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."}}