{"id":"W2921873362","doi":"10.1016/j.cam.2019.03.018","title":"Optimal weighted upwind finite volume method for convection–diffusion equations in 2D","year":2019,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"NSAF Joint Fund; Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Upwind scheme; Polygon mesh; Convection–diffusion equation; Finite volume method; Norm (philosophy); Applied mathematics; Péclet number; Convection; Numerical analysis; Mathematical analysis; Geometry; Mechanics","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":[0.0007531974,0.0007386418,0.001191376,0.0006405291,0.0004372906,0.0007661544,0.001293555,0.001357279,0.002909956],"category_scores_gemma":[0.001942042,0.0004939573,0.0006930418,0.0004176546,0.0007992226,0.001164098,0.001593902,0.001124381,0.0003917782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000413762,"about_ca_system_score_gemma":0.001304024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003985733,"about_ca_topic_score_gemma":0.003715204,"domain_scores_codex":[0.9997047,0.0001129759,0.00001985975,0.00003886074,0.00009274686,0.00003089094],"domain_scores_gemma":[0.9994482,0.0002545655,0.00005580002,0.00003687361,0.0001567034,0.0000478565],"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":[0.0002384053,0.0001778071,0.0009472109,0.0003544679,0.00009065802,0.000170837,0.0001325523,0.8646955,0.01580582,0.04772741,0.001967615,0.06769165],"study_design_scores_gemma":[0.000007560917,0.00001314434,0.00003223037,0.000004410072,0.000003933089,0.00000571243,0.000003683551,0.9973329,0.0003482499,0.001802976,0.0004409287,0.000004111188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02269679,0.0003841351,0.9738938,0.0001539579,0.0002112214,0.00006229347,0.00005008768,0.0001307768,0.00241691],"genre_scores_gemma":[0.3775289,0.0005501761,0.6115023,0.0002589658,0.0002550796,0.0004499885,0.0002839422,0.0003808917,0.008789791],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003985733,"threshold_uncertainty_score":0.009734809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01890862751357933,"score_gpt":0.2961946538487523,"score_spread":0.277286026335173,"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."}}