{"id":"W2968371227","doi":"10.1063/1.5098813","title":"Conditional dynamic subfilter modeling","year":2019,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Sandia National Laboratories; Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; Compute Canada","keywords":"Homogeneity (statistics); Statistical physics; Physics; Large eddy simulation; Turbulence; Closure (psychology); Grid; Set (abstract data type); Applied mathematics; Mechanics; Mathematics; Statistics; Computer science; 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":[0.00002466432,0.00007006712,0.0000987796,0.00002416938,0.000009619007,0.000006428559,0.00007308897,0.0000268822,0.00009775905],"category_scores_gemma":[0.000001458153,0.00007816352,0.00005429159,0.00006480523,0.00001168938,0.00008956278,0.00001475298,0.00007380345,0.0001373529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002482666,"about_ca_system_score_gemma":0.000007226038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001293904,"about_ca_topic_score_gemma":4.347682e-7,"domain_scores_codex":[0.9996263,0.000003141323,0.0001092974,0.00006827525,0.00009957869,0.00009345637],"domain_scores_gemma":[0.9997833,0.00001276388,0.000008114698,0.0001366677,0.00003679228,0.00002239516],"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":[0.000002743598,0.00001677864,0.000307991,0.00005444007,0.00002335109,2.354406e-7,0.00007757008,0.9340307,0.04461581,0.01956185,0.00005639508,0.00125212],"study_design_scores_gemma":[0.0001604357,0.000008118143,0.0002766097,0.00001118786,0.00000526589,5.523369e-7,0.0000119507,0.9901661,0.0006262893,0.008589233,0.00005665197,0.00008759642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7245561,0.00003489382,0.2720238,0.000009184383,0.0001859163,0.00004640667,0.00002488785,0.00007908224,0.003039765],"genre_scores_gemma":[0.9991024,0.00001401745,0.0006402113,0.00001768769,0.0000315088,0.000002369677,0.00007876764,0.00001736339,0.00009571008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2745463,"threshold_uncertainty_score":0.3187416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007317077020351731,"score_gpt":0.208610601885958,"score_spread":0.2012935248656063,"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."}}