{"id":"W2903885922","doi":"10.1016/j.compfluid.2018.12.003","title":"On the influence of uncertainty in computational simulations of a high-speed jet flow from an aircraft exhaust","year":2018,"lang":"en","type":"article","venue":"Computers & Fluids","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Seventh Framework Programme","keywords":"Computational fluid dynamics; Reynolds-averaged Navier–Stokes equations; Turbulence; Jet (fluid); Uncertainty quantification; Computer science; Flow (mathematics); Mechanics; Computation; Statistical physics; Physics; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00177275,0.0008551641,0.000978221,0.001004376,0.001285088,0.001717153,0.001005801,0.002473063,0.001081646],"category_scores_gemma":[0.01747533,0.0006427948,0.0009260424,0.0005459904,0.001938349,0.001194069,0.001153048,0.001760365,0.00008105447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009430872,"about_ca_system_score_gemma":0.0008288378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02308497,"about_ca_topic_score_gemma":0.009271643,"domain_scores_codex":[0.9991665,0.0004040735,0.0000437942,0.00007205762,0.0001864032,0.0001271141],"domain_scores_gemma":[0.9817026,0.0161556,0.0005810226,0.0003042076,0.0008869276,0.0003696466],"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":[0.000103795,0.00006649113,0.001225991,0.00002605323,0.00002137622,0.00006905746,0.00003621816,0.9959044,0.0006615833,0.0009226917,0.00009919894,0.0008631364],"study_design_scores_gemma":[0.000005620435,0.00002468967,0.0003625799,0.000003572573,0.000005616749,0.000003728521,0.00001324968,0.999011,0.0003343599,0.0002019992,0.0000287658,0.000004810871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9633127,0.0006171703,0.02334014,0.001189183,0.0001283855,0.00004888343,0.0001848081,0.0001429212,0.01103587],"genre_scores_gemma":[0.9979587,0.00007524369,0.00145887,0.00004766775,0.00002043268,0.00001184354,0.0000429217,0.00002964568,0.0003546011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02308497,"threshold_uncertainty_score":0.04590118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709315649059977,"score_gpt":0.312776921980276,"score_spread":0.2656837654896763,"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."}}