{"id":"W2317853655","doi":"10.2514/6.2013-2065","title":"Parameterization and optimization of broadband noise for high-lift devices","year":2013,"lang":"en","type":"article","venue":"","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Compute Canada","keywords":"Broadband; Computer science; Lift (data mining); Noise (video); Acoustics; Electronic engineering; Telecommunications; Engineering; Physics; Artificial intelligence","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":[0.00002558894,0.00005352439,0.00007352931,0.00002520956,0.00001661518,0.00002343739,0.00003016665,0.00003648429,0.00005196838],"category_scores_gemma":[0.00001292403,0.00004814793,0.000009271842,0.00003775896,0.00001191897,0.00009472718,0.000007868838,0.00001604616,0.000001151658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004762307,"about_ca_system_score_gemma":0.000001880954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001671767,"about_ca_topic_score_gemma":0.000005450823,"domain_scores_codex":[0.9997274,0.000002141879,0.0001120367,0.00005936361,0.00003387784,0.00006520588],"domain_scores_gemma":[0.9998203,0.00003553034,0.00001815099,0.000059167,0.00004653814,0.00002032742],"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":[9.63658e-7,0.000004820103,0.0002634113,0.00009304126,0.00000933898,1.931189e-8,0.00002122466,0.9903722,0.005537639,0.001220052,0.0001467736,0.002330452],"study_design_scores_gemma":[0.0001389721,0.00001814917,0.0009257898,0.000009073834,0.000009562164,3.055725e-7,0.00001300771,0.9974354,0.0009151123,0.0004390702,0.00003379328,0.00006174695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.337512,0.00003132155,0.6619042,0.00001415134,0.00007165944,0.000140989,0.000006765859,0.0000356884,0.0002832536],"genre_scores_gemma":[0.866302,0.00006233966,0.1334927,0.00001487177,0.00001821625,0.00001956017,0.00002531578,0.00001188023,0.00005318343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5287899,"threshold_uncertainty_score":0.1963416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005549817710578344,"score_gpt":0.1914815671763304,"score_spread":0.1859317494657521,"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."}}