{"id":"W2052968987","doi":"10.1121/1.4805994","title":"A robust numerical approach for prediction of turbofan engine noise","year":2013,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Turbofan; Turbulence; Takeoff; Jet engine; Acoustics; Nozzle; Jet noise; Noise (video); Jet (fluid); Computer science; Intermittency; Computational fluid dynamics; Sound pressure; Computational aeroacoustics; Simulation; Aeroacoustics; Physics; Mechanics; Aerospace engineering; Engineering","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":[0.001107605,0.0008222093,0.0008663421,0.000619932,0.0005243687,0.001064625,0.001233117,0.001545213,0.001086629],"category_scores_gemma":[0.002937325,0.00049646,0.0009333765,0.0003051743,0.00101322,0.0006609232,0.001007395,0.001148714,0.000291484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007238235,"about_ca_system_score_gemma":0.001528229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007418103,"about_ca_topic_score_gemma":0.002494656,"domain_scores_codex":[0.9996154,0.0001159304,0.00002133549,0.00004833132,0.0001648007,0.00003410829],"domain_scores_gemma":[0.9991884,0.0003911426,0.000118601,0.00006280801,0.0002012359,0.00003781237],"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":[0.00001843676,0.0000137576,0.0002199059,0.00001739672,0.00001218572,0.00002845944,0.000009907761,0.9917004,0.002651858,0.002828604,0.00005307409,0.002446112],"study_design_scores_gemma":[0.000001144658,0.000003691527,0.00001406096,6.549537e-7,6.901098e-7,9.565185e-7,5.275444e-7,0.9997003,0.0001204557,0.0001329504,0.00002354342,9.557945e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06296563,0.0003563296,0.9320893,0.00018539,0.0001013287,0.00008963027,0.0001013127,0.0005084525,0.003602569],"genre_scores_gemma":[0.8180939,0.0003636189,0.1781616,0.00007189612,0.00008377818,0.0003191601,0.0001665623,0.0001711296,0.002568314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007418103,"threshold_uncertainty_score":0.01474983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108849975180818,"score_gpt":0.1947839296362915,"score_spread":0.1836954298844834,"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."}}