{"id":"W2621311892","doi":"10.2514/6.2017-4298","title":"A NURBS-Enhanced Treatment of Curved Boundary Integrating for the Time-Accurate Upwind Scheme with Unstructured Grids","year":2017,"lang":"en","type":"article","venue":"23rd AIAA Computational Fluid Dynamics Conference","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Upwind scheme; Scheme (mathematics); Boundary (topology); Unstructured grid; Computer science; Mesh generation; Applied mathematics; Grid; Computational science; Mathematical optimization; Algorithm; Geometry; Mathematics; Mathematical analysis; Physics; Finite element method; Discretization","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001514337,0.0004234316,0.0004609541,0.00009596237,0.0006971301,0.0004250147,0.0006002486,0.0001036486,0.00002791082],"category_scores_gemma":[0.00007493704,0.000316164,0.0001638205,0.0001326648,0.0003261282,0.0002779853,0.00006738365,0.0001529751,0.000007630666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002778675,"about_ca_system_score_gemma":0.0003326033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005022224,"about_ca_topic_score_gemma":0.0003409554,"domain_scores_codex":[0.9983212,0.00002858781,0.0005351263,0.0003888694,0.0003690593,0.0003571602],"domain_scores_gemma":[0.9978549,0.0006016201,0.0002470139,0.000512714,0.0006878447,0.00009584052],"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":[0.0001312532,0.0000648144,0.0003362256,0.00006303369,0.0003560684,0.000003273748,0.0003198337,0.8788092,0.003037235,0.09289023,0.00003295193,0.02395595],"study_design_scores_gemma":[0.001319409,0.000249117,0.008592539,0.00008939514,0.00005587707,0.00001366103,0.00007213769,0.9788806,0.0001258683,0.01015273,0.00008591417,0.0003627519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3194655,0.00009102487,0.6779887,0.0002788173,0.0003536999,0.0005764824,0.000511002,0.00009889617,0.0006359109],"genre_scores_gemma":[0.9542887,0.00004686221,0.04442136,0.00002270662,0.00009894553,0.00009025235,0.0007883958,0.00005974133,0.0001829935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6348233,"threshold_uncertainty_score":0.9999291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01264735379150893,"score_gpt":0.2430969869968501,"score_spread":0.2304496332053411,"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."}}