{"id":"W2322739790","doi":"10.1103/physreve.93.033115","title":"Energy dissipation scaling in uniformly sheared turbulence","year":2016,"lang":"en","type":"article","venue":"Physical review. E","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Physics; Dissipation; Scaling; Turbulence kinetic energy; Kinetic energy; Reynolds number; Lambda; Scaling law; K-epsilon turbulence model; Physical constant; Energy (signal processing); Classical mechanics; Mathematical physics; Statistical physics; Mechanics; Quantum mechanics; Geometry; Mathematics","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":[0.0000685291,0.0001129262,0.0001976646,0.00003090197,0.00001342506,0.000008946954,0.0001069796,0.00002055856,0.00002384698],"category_scores_gemma":[0.00003335119,0.00007524362,0.00006791587,0.0001703535,0.00001419058,0.0001298598,0.00002138722,0.00005698997,0.0000649042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005783784,"about_ca_system_score_gemma":0.000006484299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001272743,"about_ca_topic_score_gemma":0.000008007925,"domain_scores_codex":[0.9993535,0.00001675026,0.0001807833,0.0001362451,0.0001245958,0.0001880914],"domain_scores_gemma":[0.9996732,0.00005290914,0.00001694197,0.0001806209,0.00001630474,0.00005997551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000972018,0.0001568843,0.001085779,0.001196838,0.00002876781,0.00001317426,0.00009422822,0.008858764,0.02592804,0.06676537,0.001525095,0.8943374],"study_design_scores_gemma":[0.0002992034,0.00002330133,0.003838156,0.00325027,0.00001742673,0.000001347352,7.731641e-7,0.9657051,0.001308895,0.01042324,0.01479968,0.0003325916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9523402,0.01629187,0.02177684,0.001052664,0.0004274502,0.0003315005,0.0000258426,0.0003455353,0.007408109],"genre_scores_gemma":[0.9869401,0.01269445,0.00008098118,0.0000902922,0.00008835051,0.00002984294,0.000006917696,0.00001860411,0.00005043593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9568464,"threshold_uncertainty_score":0.3068346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00709987769006537,"score_gpt":0.2447077809778427,"score_spread":0.2376079032877773,"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."}}