{"id":"W2326473101","doi":"10.2514/6.2011-3695","title":"Parallel High-Order Anisotropic Block-Based Adaptive Mesh Refinement Finite-Volume Scheme","year":2011,"lang":"en","type":"article","venue":"20th AIAA Computational Fluid Dynamics Conference","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite volume method; Adaptive mesh refinement; Computer science; Scheme (mathematics); Block (permutation group theory); Volume (thermodynamics); Mesh generation; Order (exchange); Computational science; Parallel computing; Finite element method; Mathematics; Physics; Geometry; Mechanics; Engineering; Mathematical analysis; Structural engineering","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":[0.0001654527,0.0005764859,0.0004730353,0.0002904471,0.0002203586,0.0001182802,0.0005422969,0.0001955168,0.0004118868],"category_scores_gemma":[0.00005009443,0.0006568611,0.0001548487,0.000553694,0.0001572252,0.0002229291,0.0001341409,0.0004003696,0.000247526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003990235,"about_ca_system_score_gemma":0.0003749132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001091284,"about_ca_topic_score_gemma":0.0002044432,"domain_scores_codex":[0.9972523,0.00006621624,0.0007563193,0.0006302649,0.0006741018,0.000620837],"domain_scores_gemma":[0.9981335,0.0002338421,0.0001235922,0.0003986786,0.0008518487,0.0002584901],"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":[0.00003531552,0.0001156535,0.0007155366,0.00003320005,0.0001007482,0.00001892799,0.00007982212,0.7152861,0.00007015102,0.2826042,0.0001727937,0.0007675503],"study_design_scores_gemma":[0.001068979,0.0001610885,0.02258568,0.00005622416,0.00003679503,0.000007749533,0.00003835937,0.9584645,0.000007577222,0.01675822,0.000123875,0.0006909498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1002333,0.00008141816,0.8943693,0.000203998,0.0006039756,0.0003776499,0.0003372605,0.0005005012,0.003292629],"genre_scores_gemma":[0.7739543,0.00002620808,0.2241303,0.0002012027,0.00006043642,0.00006521536,0.001164218,0.00007669257,0.0003213505],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6737211,"threshold_uncertainty_score":0.9995883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01797014390069631,"score_gpt":0.2044223199685474,"score_spread":0.1864521760678511,"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."}}