{"id":"W4214938490","doi":"10.1063/5.0083074","title":"Deep structured neural networks for turbulence closure modeling","year":2022,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reynolds-averaged Navier–Stokes equations; Turbulence modeling; Reynolds stress; Turbulence; Physics; Tensor (intrinsic definition); Large eddy simulation; Reynolds stress equation model; Cauchy stress tensor; Statistical physics; Turbulence kinetic energy; Mechanics; Applied mathematics; Classical mechanics; K-omega turbulence model; Mathematics; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00007524599,0.0001527025,0.0002141333,0.0000212784,0.0002646077,0.00001797923,0.0002368601,0.00002090282,0.0001644118],"category_scores_gemma":[0.000001225925,0.0001573504,0.0002153498,0.000169548,0.00002982109,0.0001096538,0.0001072386,0.0002508221,3.966675e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001448282,"about_ca_system_score_gemma":0.0000191018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002417606,"about_ca_topic_score_gemma":2.665637e-7,"domain_scores_codex":[0.9990334,0.00003771508,0.0002335063,0.0002485177,0.0001852813,0.0002615813],"domain_scores_gemma":[0.9995099,0.00003477698,0.00008768059,0.000233862,0.00007464476,0.00005916596],"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":[0.00005087373,0.00004890127,0.00032481,0.000007143266,0.00003486787,1.094358e-7,0.0001225206,0.9591744,0.0006141189,0.01931454,0.0003457779,0.01996195],"study_design_scores_gemma":[0.0003747097,0.00006487639,0.000008726046,0.000002846492,0.00002771452,5.567094e-7,0.0001166001,0.9732943,0.0004428978,0.02530556,0.0002089092,0.0001522922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2296057,0.0001827916,0.768916,0.00009061988,0.0006084028,0.0002674142,0.00004516996,0.00002958837,0.0002543785],"genre_scores_gemma":[0.9976553,0.000002722526,0.000976492,0.00006887902,0.001000648,0.00009504695,0.0001116075,0.00002716727,0.00006213767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7680497,"threshold_uncertainty_score":0.6416563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01947000138151381,"score_gpt":0.2507756438838387,"score_spread":0.2313056425023249,"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."}}