{"id":"W4300663545","doi":"10.48550/arxiv.1702.07749","title":"Well-balanced mesh-based and meshless schemes for the shallow-water\\n equations","year":2017,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Consistency (knowledge bases); Shallow water equations; Mathematics; Polygon mesh; Applied mathematics; Finite difference; Derivative (finance); Finite difference method; Momentum (technical analysis); Mathematical analysis; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006967928,0.0007033718,0.0007836021,0.0001906086,0.001129915,0.000220609,0.001481993,0.0004143044,0.00009377088],"category_scores_gemma":[0.0008638785,0.0006123601,0.0003934377,0.0002007188,0.0006035355,0.0002885401,0.0007653447,0.0007828291,0.00005192475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002899132,"about_ca_system_score_gemma":0.0001291813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001481144,"about_ca_topic_score_gemma":0.000011237,"domain_scores_codex":[0.9974265,0.0001504429,0.0005051729,0.001087183,0.0001708533,0.0006598469],"domain_scores_gemma":[0.9918683,0.005550159,0.000421934,0.001546026,0.0003795293,0.0002340767],"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":[0.00008382759,0.00006660162,0.0001296151,0.0007277725,0.0003577928,0.00001541405,0.0001638105,0.8717188,0.0001556496,0.1236415,0.00001578821,0.002923418],"study_design_scores_gemma":[0.0009409106,0.00004427112,0.00009100787,0.0002521592,0.0004208433,0.000001542106,0.0001101054,0.7655963,0.0006788943,0.2290648,0.002213084,0.0005860801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01396384,0.0002702694,0.9817673,0.0004392061,0.0009710563,0.001429779,0.00009147515,0.0002065351,0.0008605199],"genre_scores_gemma":[0.8752387,0.0004164875,0.1231972,0.00006873018,0.0001781114,0.00002603069,0.00004137449,0.0001028342,0.00073048],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8612749,"threshold_uncertainty_score":0.9996328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335922960678516,"score_gpt":0.259657702844189,"score_spread":0.1260654067763374,"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."}}