{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009557679,0.0006626504,0.000601213,0.0004557397,0.0003331403,0.001026184,0.00177561,0.000788542,0.002061821],"category_scores_gemma":[0.002439067,0.0003122268,0.0008627299,0.0003315485,0.000641112,0.001488122,0.001245039,0.001111187,0.000331556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009248728,"about_ca_system_score_gemma":0.001024808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00512482,"about_ca_topic_score_gemma":0.003729969,"domain_scores_codex":[0.9994804,0.00009633326,0.00002386356,0.0001113496,0.0002286049,0.00005947686],"domain_scores_gemma":[0.9991149,0.0003261025,0.0001140872,0.0001724219,0.0002045125,0.00006795318],"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":[0.00006847896,0.00004054544,0.0009904754,0.00003768447,0.00004376438,0.00006562297,0.00003938195,0.899173,0.01112512,0.07119025,0.001030908,0.01619467],"study_design_scores_gemma":[0.000001046203,0.000004011314,0.0000440443,6.750802e-7,0.000001634085,0.000004055189,6.565035e-7,0.9977489,0.0005800595,0.001419556,0.0001931622,0.000002140594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01669999,0.00007187112,0.9802684,0.00008580438,0.00004667533,0.00002516901,0.0001039535,0.000491838,0.002206278],"genre_scores_gemma":[0.8303123,0.0001902021,0.1629514,0.0001693817,0.00008200558,0.0001509354,0.0004588371,0.0004937866,0.005191359],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00512482,"threshold_uncertainty_score":0.01018995,"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."}}