{"id":"W2312683890","doi":"10.2514/6.2016-0836","title":"Discretization Error Estimation by the Error Transport Equation on Unstructured Meshes - Applications to Viscous Flows","year":2016,"lang":"en","type":"article","venue":"54th AIAA Aerospace Sciences Meeting","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discretization; Polygon mesh; Discretization error; Computer science; Estimation; Applied mathematics; Mathematical optimization; Algorithm; Computational science; Mathematics; Computer graphics (images); Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002405525,0.0007499784,0.0009564857,0.00115777,0.0004672498,0.001595166,0.0010741,0.001990911,0.0009794231],"category_scores_gemma":[0.01468548,0.0005590911,0.0007678202,0.0006675609,0.001430462,0.00196694,0.001469991,0.001368034,0.0002189165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007061562,"about_ca_system_score_gemma":0.0007828197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003916259,"about_ca_topic_score_gemma":0.001591749,"domain_scores_codex":[0.9990838,0.0004239572,0.00007646139,0.0001002671,0.0002681349,0.00004747468],"domain_scores_gemma":[0.9952499,0.002964635,0.0003376977,0.0002999178,0.001050086,0.00009778034],"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":[0.0002788273,0.0001112482,0.001909497,0.0002511837,0.00006095945,0.0001556651,0.0001605283,0.8330708,0.0211529,0.07168262,0.001610881,0.06955485],"study_design_scores_gemma":[0.000004091095,0.00000968416,0.0000793334,0.000007856853,0.000002623955,0.00000995442,0.000006782714,0.9948258,0.001561303,0.003239613,0.0002469773,0.000005935196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02539921,0.0002922269,0.9725577,0.000300151,0.0001312643,0.00002739588,0.00002914605,0.0001157647,0.001147146],"genre_scores_gemma":[0.600629,0.000948216,0.3880406,0.0001567152,0.0002052323,0.0001247491,0.0002390565,0.000358596,0.009297801],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003916259,"threshold_uncertainty_score":0.01272178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03508345913632258,"score_gpt":0.322640818331607,"score_spread":0.2875573591952844,"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."}}