{"id":"W4413177607","doi":"10.1137/24m1675588","title":"Monolithic Multigrid Preconditioners for High-Order Discretizations of Stokes Equations","year":2025,"lang":"en","type":"article","venue":"SIAM Journal on Scientific Computing","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Sandia National Laboratories; Natural Sciences and Engineering Research Council of Canada; National Centre for Supercomputing Applications; National Science Foundation","keywords":"Multigrid method; Mathematics; Applied mathematics; Discretization; Order (exchange); Navier–Stokes equations; Mathematical analysis; Computational science; Partial differential equation; Compressibility; Mechanics; Physics","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":[0.0007049637,0.0001185874,0.0002012203,0.0003812892,0.0004244412,0.0001202636,0.0002115315,0.00003977775,0.0000166755],"category_scores_gemma":[0.001323796,0.0001133746,0.00008106136,0.0008514443,0.000108466,0.0001290185,0.0000320826,0.0002112713,0.000004285157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009004988,"about_ca_system_score_gemma":0.00006874605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.556005e-7,"about_ca_topic_score_gemma":4.439738e-7,"domain_scores_codex":[0.9987837,0.00005653363,0.0005582919,0.0001648548,0.000237867,0.0001987733],"domain_scores_gemma":[0.9970283,0.002192915,0.0001741372,0.0001673025,0.0003789278,0.00005841263],"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":[0.000002535331,0.00003802343,0.0000160656,0.00008407301,0.00003919064,2.22422e-7,0.0002440827,0.9278164,0.001142277,0.05238924,0.0004036504,0.01782426],"study_design_scores_gemma":[0.0002850763,0.00002358391,0.0002480944,0.0002560563,0.00002123784,0.00000244505,0.000163532,0.8642653,0.002648021,0.1313355,0.0006417378,0.0001094638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01957075,0.00009378455,0.9767314,0.0001819529,0.002581079,0.0002251014,0.0000288093,0.00008531395,0.0005017677],"genre_scores_gemma":[0.5412847,0.00000218717,0.4584729,0.00001983192,0.00006549836,0.000004631683,0.00001151244,0.00001238527,0.0001263529],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.521714,"threshold_uncertainty_score":0.4623283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02616081397696043,"score_gpt":0.3391272034012381,"score_spread":0.3129663894242777,"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."}}