{"id":"W2021631650","doi":"10.1007/s00791-006-0056-3","title":"Monotonicity preserving multigrid time stepping schemes for conservation laws","year":2007,"lang":"en","type":"article","venue":"Computing and Visualization in Science","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conservation law; Multigrid method; Mathematics; Scalar (mathematics); Monotonic function; Applied mathematics; Nonlinear system; Total variation diminishing; Interpolation (computer graphics); Residual; Mathematical optimization; Riemann problem; Riemann hypothesis; Mathematical analysis; Algorithm; Partial differential equation; Computer science; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001528461,0.00008232242,0.0001146989,0.0001549779,0.0001679724,0.00005488699,0.0001311714,0.00003064398,0.000001357509],"category_scores_gemma":[0.001160105,0.00008915387,0.00001171388,0.0006854489,0.0001105098,0.0002298844,0.00006174282,0.00005519814,9.884899e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006546307,"about_ca_system_score_gemma":0.00001791859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001714373,"about_ca_topic_score_gemma":9.401367e-7,"domain_scores_codex":[0.9991248,0.00001635276,0.000292578,0.0001860233,0.000165363,0.000214836],"domain_scores_gemma":[0.9986296,0.0010397,0.00006299104,0.00008267046,0.0001361549,0.00004885057],"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":[0.00002779968,0.00008349994,0.01487472,0.0007089109,0.00001127743,0.000001370444,0.003488609,0.7337766,0.05800143,0.05435844,0.00008461432,0.1345827],"study_design_scores_gemma":[0.0001661896,0.00001509324,0.003983769,0.00009310646,0.000001428657,0.000001347665,0.00006101367,0.9856724,0.005314011,0.00433336,0.0002530956,0.0001052034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2979278,0.00004964077,0.7015044,0.00000985002,0.0001043288,0.0001523274,5.426232e-7,0.0001160022,0.0001350709],"genre_scores_gemma":[0.5779293,0.000003165196,0.4219736,0.00004337177,0.00003114996,0.000002804785,0.000001562881,0.000009061754,0.000006014795],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2800015,"threshold_uncertainty_score":0.3635589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03336873009052612,"score_gpt":0.3894328332980712,"score_spread":0.3560641032075451,"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."}}