{"id":"W4317581638","doi":"10.2514/6.2023-0988","title":"Estimation of Skin Friction on the NASA BeVERLI Hill using Oil Film Interferometry","year":2023,"lang":"en","type":"article","venue":"AIAA SCITECH 2023 Forum","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Reynolds-averaged Navier–Stokes equations; Drag; Parasitic drag; Interferometry; Boundary layer; Computational fluid dynamics; Marine engineering; Velocimetry; Wind tunnel; Laser Doppler velocimetry; Turbulence; Flow (mathematics); Benchmark (surveying); Pressure measurement; Mechanical engineering; Computer science; Aerospace engineering; Mechanics; Optics; Engineering; Physics; Geology; Geodesy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029912,0.0001328118,0.0001301085,0.0003104504,0.00009738281,0.00003379821,0.0001719351,0.00009143609,0.00008463256],"category_scores_gemma":[0.00008380183,0.0001083393,0.00008231115,0.001024747,0.00002443776,0.0001134784,0.00006761073,0.0001765284,0.0001680676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008157711,"about_ca_system_score_gemma":0.00001035541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005168288,"about_ca_topic_score_gemma":0.00001669496,"domain_scores_codex":[0.9991155,0.00001971587,0.0002362381,0.0001473305,0.0002210215,0.0002602387],"domain_scores_gemma":[0.9995065,0.0001149564,0.00004028816,0.0002707941,0.00002636903,0.00004105814],"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":[0.000006261419,0.00001533908,0.0001252191,0.00006334532,0.00004552728,0.000002618707,0.0001144329,0.9569395,0.007102221,0.0026824,0.008204652,0.02469854],"study_design_scores_gemma":[0.0001030294,0.0000374732,0.0006065466,0.00009485389,0.000009478043,0.000001941422,0.00007547037,0.9939597,0.003595943,0.0006445185,0.0007592786,0.0001117686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896618,0.00005595684,0.006013616,0.0004344381,0.001052482,0.0001001641,0.00005171456,0.000324235,0.002305644],"genre_scores_gemma":[0.9988827,0.00005345208,0.0003138166,0.00005539027,0.00003942014,0.00001381777,0.00004232018,0.00003505386,0.0005640021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03702026,"threshold_uncertainty_score":0.4417949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267729796861843,"score_gpt":0.222755530847253,"score_spread":0.2100782328786346,"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."}}