{"id":"W2569335350","doi":"10.2514/6.2017-1947","title":"A Truncation Error Based Anisotropic Mesh Adaptation Metric for CFD","year":2017,"lang":"en","type":"article","venue":"55th AIAA Aerospace Sciences Meeting","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Truncation error; Truncation (statistics); Computational fluid dynamics; Metric (unit); Computer science; Algorithm; Mesh generation; Adaptation (eye); Mathematical optimization; Applied mathematics; Mathematics; Finite element method; Physics; Mechanics; Engineering; Optics; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00138024,0.0007196698,0.0007238204,0.0008642174,0.000386511,0.0009428693,0.001208263,0.0009462237,0.001373065],"category_scores_gemma":[0.00538692,0.0003249104,0.0005966622,0.0007285574,0.0007004514,0.001068077,0.001517861,0.00182074,0.0005491737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006052096,"about_ca_system_score_gemma":0.0008569142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001912251,"about_ca_topic_score_gemma":0.001823798,"domain_scores_codex":[0.9988187,0.0003470966,0.00008126751,0.00009512867,0.0006096901,0.00004798567],"domain_scores_gemma":[0.9980314,0.0005226653,0.0001760277,0.0003523313,0.0007917837,0.0001257234],"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":[0.0003723035,0.0001449657,0.001232635,0.0002242824,0.00005592289,0.0001367648,0.0001215885,0.4969438,0.07266328,0.08854295,0.007477677,0.3320839],"study_design_scores_gemma":[0.000004360237,0.00003413056,0.0001282674,0.000006475035,0.00000415923,0.00003689978,0.00000599141,0.9898712,0.004044131,0.00373934,0.00211297,0.00001208739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006022872,0.0001836828,0.9920621,0.00008340092,0.0001059926,0.00002853026,0.00004291331,0.0001712843,0.0012992],"genre_scores_gemma":[0.2242529,0.0006011854,0.7694507,0.0001457926,0.0001635602,0.0001324855,0.0003080877,0.0004497478,0.004495512],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001912251,"threshold_uncertainty_score":0.007299483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06892399952700047,"score_gpt":0.3492177227852002,"score_spread":0.2802937232581997,"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."}}