{"id":"W2052302115","doi":"10.1121/1.4907163","title":"A hybrid finite element–transfer matrix model for vibroacoustic systems with flat and homogeneous acoustic treatments","year":2015,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Acoustic Wave Phenomena Research","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; Université de Sherbrooke","funders":"","keywords":"Finite element method; Dissipative system; Reduction (mathematics); Computer science; Transfer matrix; Matrix (chemical analysis); Homogeneous; Structural acoustics; Acoustics; Transfer-matrix method (optics); Degrees of freedom (physics and chemistry); Poromechanics; Vibration; Mathematics; Physics; Structural engineering; Materials science; Geometry; Engineering; Statistical physics; Porous medium","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":[0.0003439562,0.0006016326,0.0006188349,0.0004195539,0.0003628036,0.0007460123,0.001463098,0.00175056,0.003898867],"category_scores_gemma":[0.0005412558,0.0003841142,0.0006233099,0.0003882574,0.0006528109,0.0007713233,0.0007063692,0.0008431235,0.0008668565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004839113,"about_ca_system_score_gemma":0.0007487875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003603406,"about_ca_topic_score_gemma":0.002963289,"domain_scores_codex":[0.9998304,0.00004499798,0.000008844291,0.00003533566,0.00006416891,0.00001634734],"domain_scores_gemma":[0.9998459,0.00007187813,0.00002039633,0.00001403686,0.00003721187,0.00001058362],"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":[0.00002879484,0.00003874621,0.0001975396,0.00007145922,0.00001469639,0.0001170089,0.00008201587,0.9582303,0.01000176,0.02206619,0.0003428528,0.008808582],"study_design_scores_gemma":[0.000003308108,0.00001486577,0.00003503907,0.000004420431,0.000003232289,0.00002163936,0.000008479958,0.9970859,0.0004883584,0.001482988,0.0008469144,0.000004860842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00857307,0.0001364309,0.984816,0.0001302491,0.00002794967,0.00004835818,0.0000734671,0.0001566326,0.006037796],"genre_scores_gemma":[0.7077507,0.000647844,0.2586854,0.0002242065,0.00005414943,0.0007281569,0.000348738,0.0001256951,0.03143499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003898867,"threshold_uncertainty_score":0.01304299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02213541781718545,"score_gpt":0.2522792663473113,"score_spread":0.2301438485301258,"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."}}