{"id":"W340692704","doi":"10.1007/978-3-540-92779-2_52","title":"Solution of Laminar Combusting Flows Using a Parallel Implicit Adaptive Mesh Refinement Algorithm","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Laminar flow; Multigrid method; Combustion; Computer science; Mathematical optimization; Adaptive mesh refinement; Algorithm; Applied mathematics; Partial differential equation; Residual; Mathematics; Computational science; Mechanics; Chemistry; Mathematical analysis; Physics","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":[0.0001258283,0.0004136259,0.0005289249,0.0002264478,0.00006395239,0.00001710269,0.0001536826,0.0003381085,0.0002779654],"category_scores_gemma":[0.000004744368,0.0004500652,0.0001970407,0.00005017628,0.00003319962,0.00006258972,0.00006635949,0.0003855419,0.00002142033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003118444,"about_ca_system_score_gemma":0.0000338799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004439442,"about_ca_topic_score_gemma":0.00007040179,"domain_scores_codex":[0.9985721,0.000008289699,0.000583294,0.0002684516,0.0002780005,0.0002899363],"domain_scores_gemma":[0.9992864,0.00003146963,0.0001521257,0.0003198749,0.0001303794,0.00007972348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003782602,0.00005890653,0.000002081521,0.0002612032,0.0004791101,0.00004376907,0.0002554595,0.2865113,0.001345624,0.1357764,0.001962651,0.5732657],"study_design_scores_gemma":[0.0003547819,0.00008877784,0.00001478737,0.0003093473,0.0001189596,0.00001911746,0.0000323058,0.9904754,0.00002164274,0.001791266,0.006312578,0.0004610236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001408288,0.0003962984,0.6285657,0.00002018489,0.0002893092,0.000372148,0.0000720994,0.000360548,0.3697829],"genre_scores_gemma":[0.01585038,0.001442539,0.6645261,0.0001732435,0.0006883623,0.00002155397,0.0005500957,0.0004566222,0.3162911],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7039641,"threshold_uncertainty_score":0.9997951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328390835073109,"score_gpt":0.2236062002617757,"score_spread":0.2003222919110446,"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."}}