{"id":"W4251387955","doi":"10.13052/17797179.2012.702428","title":"Hierarchical elements for the iterative solving of turbulent flow problems on anisotropic meshes","year":2012,"lang":"en","type":"article","venue":"European Journal of Computational Mechanics","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polygon mesh; Mathematical optimization; Computer science; Iterative method; Convergence (economics); Anisotropy; Applied mathematics; Flow (mathematics); Quadratic equation; Algorithm; Computational science; Mathematics; Geometry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007462868,0.0004275255,0.0003681803,0.0004782387,0.000352135,0.000446606,0.0007424697,0.0005038017,0.001854289],"category_scores_gemma":[0.002019766,0.0003082408,0.0005552285,0.0007362559,0.0006905661,0.0005200947,0.001134812,0.001088113,0.0007024485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004748093,"about_ca_system_score_gemma":0.0007517636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002524972,"about_ca_topic_score_gemma":0.003913318,"domain_scores_codex":[0.9994611,0.000195488,0.0000255646,0.00002540928,0.0002590986,0.00003323154],"domain_scores_gemma":[0.999451,0.0002973565,0.00003870137,0.00007186715,0.0001109607,0.00003008954],"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":[0.0001068366,0.00008160554,0.0008088451,0.0002964956,0.00003712066,0.0001128813,0.000496997,0.5163465,0.03495176,0.3066709,0.004257941,0.1358321],"study_design_scores_gemma":[0.00001083229,0.00002450545,0.00009755922,0.00001467282,0.000005068442,0.00001809072,0.00002070074,0.9687649,0.002084377,0.02389694,0.005055387,0.000007085001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00479967,0.0001342837,0.9931216,0.00005525597,0.00002333791,0.00003220797,0.0000262861,0.0001369529,0.001670434],"genre_scores_gemma":[0.1559896,0.0003694348,0.8383608,0.00006660272,0.00003308403,0.00022016,0.0001788155,0.0002008843,0.004580626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002524972,"threshold_uncertainty_score":0.006203234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03070600938848008,"score_gpt":0.2590724698536082,"score_spread":0.2283664604651281,"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."}}