{"id":"W4401442166","doi":"10.1121/10.0028195","title":"An impedance tube technique for estimating the insertion loss of earplugs","year":2024,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Test fixture; Acoustics; Electrical impedance; Reflection coefficient; Insertion loss; Acoustic impedance; Reflection (computer programming); Transfer-matrix method (optics); Materials science; Input impedance; Mathematics; Computer science; Optics; Physics; Engineering; Ultrasonic sensor; Electrical engineering; Statistics","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":[0.001314729,0.00009067409,0.0001881079,0.00001379,0.0002067478,0.00006216561,0.001385605,0.00004135944,0.000002589306],"category_scores_gemma":[0.0002220359,0.0000394843,0.0002808394,0.0004070901,0.0004152547,0.0002722747,0.0001508226,0.0003323442,4.673163e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003447031,"about_ca_system_score_gemma":0.000163522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001083867,"about_ca_topic_score_gemma":9.002603e-8,"domain_scores_codex":[0.998903,0.00009470909,0.0003699731,0.0000921262,0.0003654114,0.0001747233],"domain_scores_gemma":[0.9983964,0.0006782236,0.0003622422,0.0003277338,0.0001948877,0.00004054332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005372364,0.0001020281,0.00004341793,0.0002910891,0.0001237314,0.000001114168,0.003504506,0.02298145,0.7321405,0.0000790847,0.004912768,0.2357666],"study_design_scores_gemma":[0.00008909006,0.000288363,0.0001370394,0.0002970453,0.00007603725,0.0001036118,0.0003534102,0.8437858,0.1451879,0.009439946,0.0001786644,0.00006313813],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01407304,0.0004232543,0.9771543,0.007977609,0.0001977631,0.0001387902,0.000002295626,0.00001808942,0.00001488808],"genre_scores_gemma":[0.5364745,0.00003853722,0.4628918,0.0004549794,0.0001247121,0.000002123449,4.619755e-8,0.000005903242,0.000007396029],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8208043,"threshold_uncertainty_score":0.2574822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221656650368144,"score_gpt":0.2897944769896127,"score_spread":0.2775779104859313,"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."}}