{"id":"W2049794979","doi":"10.1007/s10915-008-9247-z","title":"Optimal Error Estimates for the Fully Discrete Interior Penalty DG Method for the Wave Equation","year":2008,"lang":"en","type":"article","venue":"Journal of Scientific Computing","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":95,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Discretization; Norm (philosophy); Discontinuous Galerkin method; Degree of a polynomial; Mathematical analysis; A priori and a posteriori; Finite element method; Applied mathematics; Error analysis; Wave equation; Polynomial","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002813231,0.001328248,0.001161437,0.001089534,0.0004360547,0.0017343,0.001242763,0.001700688,0.003680054],"category_scores_gemma":[0.01016812,0.0004881113,0.0005401439,0.0004700613,0.001699119,0.001841858,0.002609368,0.002640383,0.0006969878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007399769,"about_ca_system_score_gemma":0.001489919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002653415,"about_ca_topic_score_gemma":0.002100114,"domain_scores_codex":[0.9991497,0.0004149764,0.00003987417,0.00006099529,0.000272673,0.00006183011],"domain_scores_gemma":[0.9960926,0.002295285,0.0002296664,0.0002645346,0.000847294,0.0002706921],"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":[0.0006439442,0.0002128361,0.00125344,0.0006149803,0.00008320043,0.0001284388,0.0002517022,0.6496512,0.01156585,0.2367564,0.004274019,0.09456398],"study_design_scores_gemma":[0.00001392605,0.00002126472,0.00006008184,0.00002054135,0.000004449836,0.0000111626,0.00001329878,0.9868879,0.0006390082,0.01171724,0.0006017477,0.000009498152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0117052,0.0002653969,0.9847496,0.0003313893,0.0001012356,0.00003184768,0.00005188983,0.0001045501,0.002658905],"genre_scores_gemma":[0.3661758,0.0007286128,0.6217989,0.0002792146,0.0002042376,0.0002840578,0.0004123375,0.0006434058,0.009473499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003680054,"threshold_uncertainty_score":0.01487797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114108910856744,"score_gpt":0.3788281257294577,"score_spread":0.2674172346437833,"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."}}