{"id":"W4320184596","doi":"10.3397/in_2022_0054","title":"Modelling of acoustic metamaterial sound insulator using a transfer matrix method for aircraft cabin applications","year":2023,"lang":"en","type":"article","venue":"NOISE-CON proceedings","topic":"Acoustic Wave Phenomena Research","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Queen's University; Université de Sherbrooke","funders":"","keywords":"Fuselage; Transfer matrix; Metamaterial; Transmission loss; Acoustics; Sound transmission class; Transfer-matrix method (optics); Helmholtz free energy; Resonator; Finite element method; Matrix (chemical analysis); Materials science; Soundproofing; Physics; Structural engineering; Engineering; Optics; Computer science; Composite material","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":[0.0001336613,0.0003819375,0.0002336668,0.0002798852,0.000168826,0.0004235562,0.0004718371,0.0007221351,0.001658852],"category_scores_gemma":[0.000246594,0.0001980792,0.0004636591,0.0002560616,0.0002377488,0.0004610427,0.0002027674,0.0002995204,0.0003558848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002537574,"about_ca_system_score_gemma":0.0004004441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001724291,"about_ca_topic_score_gemma":0.001524326,"domain_scores_codex":[0.9999378,0.00001819378,0.000002168124,0.000008354627,0.00002620416,0.000007312856],"domain_scores_gemma":[0.9999161,0.00004465619,0.00001137286,0.000008146763,0.00001622348,0.000003572455],"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":[0.00004794231,0.00007475656,0.0005378671,0.0001644205,0.00002983334,0.0002653089,0.00009363948,0.8640834,0.108042,0.01201599,0.0003243624,0.01432052],"study_design_scores_gemma":[0.000002613193,0.00001612665,0.00007556545,0.000003744682,0.000002595036,0.00002343491,0.00001225961,0.9946307,0.004201983,0.0004028338,0.0006246904,0.000003516999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1112814,0.000306465,0.8765937,0.0001103916,0.00003764476,0.00006665085,0.0001159981,0.0004054483,0.01108233],"genre_scores_gemma":[0.8186276,0.0005850034,0.1728706,0.00002667511,0.0000145409,0.0001743764,0.0001284153,0.00009833484,0.007474545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001724291,"threshold_uncertainty_score":0.005549431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05557824408211547,"score_gpt":0.3148523328226404,"score_spread":0.2592740887405249,"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."}}