{"id":"W4296077684","doi":"10.1007/s10915-022-01990-w","title":"Accurate High-Order Tensor-Product Generalized Summation-By-Parts Discretizations of Hyperbolic Conservation Laws: General Curved Domains and Functional Superconvergence","year":2022,"lang":"en","type":"article","venue":"Journal of Scientific Computing","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Superconvergence; Mathematics; Conservation law; Tensor product; Order (exchange); Tensor (intrinsic definition); Product (mathematics); Mathematical analysis; Summation by parts; Applied mathematics; Pure mathematics; Finite element method; 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":[0.001079514,0.0001338018,0.0002826754,0.0002042428,0.0004352732,0.00007300077,0.0001720692,0.00002101607,0.00009164339],"category_scores_gemma":[0.0003380059,0.0001324477,0.00006103617,0.0008431491,0.0001570923,0.0002904881,0.0001087634,0.0002189716,9.829339e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008528773,"about_ca_system_score_gemma":0.00006767971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005458404,"about_ca_topic_score_gemma":9.208862e-7,"domain_scores_codex":[0.9981465,0.0001682763,0.0007815248,0.0001892715,0.0005380207,0.0001764606],"domain_scores_gemma":[0.9984223,0.0004711002,0.0003683667,0.0001488823,0.000513927,0.00007545216],"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":[0.000008843781,0.00004290858,0.000886326,0.00005137566,0.0000441101,0.000001530219,0.000320696,0.9485177,0.04347916,0.00326699,0.001755448,0.001624884],"study_design_scores_gemma":[0.0005419043,0.00003945235,0.004967912,0.00003721841,0.00003504371,0.00007891565,0.0002266978,0.9789149,0.003018935,0.01027561,0.001666577,0.0001968428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5437059,0.0002188842,0.4545387,0.0002001582,0.001206321,0.00007392991,0.00002176984,0.00002286837,0.00001144079],"genre_scores_gemma":[0.7782663,0.00001563541,0.2214366,0.00003665849,0.0001305264,0.000003035467,0.00003243257,0.00001855745,0.00006023232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2345604,"threshold_uncertainty_score":0.5401062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730961000333815,"score_gpt":0.2710205060748465,"score_spread":0.2437108960715083,"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."}}