{"id":"W4407717108","doi":"10.1002/num.70001","title":"An Algebraic Preconditioner for the Exactly Divergence‐Free Discontinuous Galerkin Method for Stokes","year":2025,"lang":"en","type":"article","venue":"Numerical Methods for Partial Differential Equations","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Laboratory Directed Research and Development; Natural Sciences and Engineering Research Council of Canada","keywords":"Preconditioner; Mathematics; Divergence (linguistics); Stokes problem; Algebraic number; Galerkin method; Discontinuous Galerkin method; Mathematical analysis; Finite element method; Pure mathematics; Applied mathematics; Physics; Linear system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009371246,0.0003824829,0.0006116126,0.0001471576,0.0006428541,0.0001327228,0.0007206097,0.0001665926,0.00009635049],"category_scores_gemma":[0.005340207,0.0003048678,0.0004773635,0.0004332163,0.0001225538,0.0002467699,0.00008021458,0.0002164021,0.000002870417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000097414,"about_ca_system_score_gemma":0.00005497472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006579704,"about_ca_topic_score_gemma":0.00000368393,"domain_scores_codex":[0.9974543,0.0004445938,0.0008221188,0.0005080156,0.0002033498,0.0005675863],"domain_scores_gemma":[0.9761525,0.02262165,0.0001718913,0.0006356688,0.0002652767,0.0001530668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001769748,0.0002867044,0.000005622246,0.0002794589,0.0004847691,7.986981e-8,0.0002442147,0.136971,0.01650803,0.2686183,0.001244089,0.5751807],"study_design_scores_gemma":[0.0006410885,0.0001543727,0.00009915936,0.00001895154,0.0003212622,4.403483e-7,0.00005352087,0.6494491,0.008458386,0.3350151,0.005542246,0.0002464887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009632246,0.0002320976,0.9926028,0.0005011366,0.002571946,0.002961123,0.0006029234,0.0003692382,0.00006246057],"genre_scores_gemma":[0.02338906,0.000009010399,0.9688089,0.000150648,0.0004963876,0.006692602,0.0001809861,0.00008775412,0.0001846856],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5749342,"threshold_uncertainty_score":0.9999403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04494633828159398,"score_gpt":0.4230632447046988,"score_spread":0.3781169064231048,"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."}}