{"id":"W2061318403","doi":"10.1002/fld.1118","title":"MPDATA error estimator for mesh adaptivity","year":2005,"lang":"en","type":"article","venue":"International Journal for Numerical Methods in Fluids","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Polygon mesh; Solver; Robustness (evolution); Computer science; Adaptive mesh refinement; Benchmark (surveying); Estimator; Euler equations; Algorithm; Mathematical optimization; Mesh generation; Compressible flow; Applied mathematics; Computational science; Mathematics; Compressibility; Finite element method; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0009532452,0.0001899501,0.0002663215,0.0002113758,0.00008123714,0.0001204176,0.000518748,0.00008826457,0.00004760411],"category_scores_gemma":[0.0006259139,0.0001890531,0.0002205218,0.0001323822,0.00002756215,0.0002884417,0.00006069635,0.0002760038,0.000006512222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003952438,"about_ca_system_score_gemma":0.00005179672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002895989,"about_ca_topic_score_gemma":0.000005868767,"domain_scores_codex":[0.9985891,0.00005800925,0.0005643919,0.0002055104,0.0002856108,0.000297368],"domain_scores_gemma":[0.9984408,0.0009850053,0.00005905591,0.0001176039,0.0002668375,0.0001307082],"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":[0.0001495549,0.0001490269,0.0002554604,0.00002255977,0.0002164521,0.000009013199,0.00007264748,0.4766439,0.005973396,0.04067093,0.004696977,0.4711401],"study_design_scores_gemma":[0.0007793965,0.0000563814,0.0006045538,0.00002893237,0.00001363663,0.00008238286,0.00001205883,0.9254492,0.0002484771,0.01832334,0.05419735,0.0002043051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004982306,0.0001846924,0.9894758,0.00133222,0.003311154,0.0002272411,0.0001715674,0.0000745592,0.0002404958],"genre_scores_gemma":[0.06901007,0.00004605189,0.9295723,0.0001862685,0.000877655,0.00006403752,0.00005526521,0.00005091692,0.0001374614],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4709358,"threshold_uncertainty_score":0.7709361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03926859276660935,"score_gpt":0.4128745059081287,"score_spread":0.3736059131415194,"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."}}