{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006835926,0.0005322942,0.0005719638,0.0004536605,0.0003619099,0.000821903,0.000483047,0.0006001207,0.004473376],"category_scores_gemma":[0.002666655,0.0002061449,0.000421332,0.0003144964,0.001247377,0.000663742,0.001393486,0.001093053,0.0009255109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004113802,"about_ca_system_score_gemma":0.0008557413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001642783,"about_ca_topic_score_gemma":0.001441959,"domain_scores_codex":[0.9992404,0.0002754731,0.0000341832,0.00007742545,0.0002986405,0.00007385114],"domain_scores_gemma":[0.9990397,0.0003536612,0.0001247088,0.0002091543,0.0002109337,0.00006181693],"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":[0.0001555019,0.00007696968,0.001088736,0.0002043371,0.00003304728,0.0001731374,0.0002255902,0.613088,0.06260522,0.2527141,0.004454623,0.06518073],"study_design_scores_gemma":[0.00001432562,0.00002856548,0.0001686649,0.000007975073,0.000002576135,0.00002085109,0.00001145554,0.9704399,0.010029,0.01582301,0.003447549,0.000006287054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06031263,0.0001784475,0.9234053,0.0003640443,0.0001971184,0.00005781879,0.00008708557,0.0005893069,0.01480824],"genre_scores_gemma":[0.7104074,0.0002634189,0.2806399,0.0001946951,0.0001376438,0.0001083901,0.0002236638,0.0002659981,0.007758916],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004473376,"threshold_uncertainty_score":0.014965,"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."}}