{"id":"W4225300656","doi":"10.1121/10.0009822","title":"Modeling the influence of COVID-19 protective measures on the mechanics of phonation","year":2022,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Institute on Deafness and Other Communication Disorders","keywords":"Phonation; Acoustics; Articulatory phonetics; Coronavirus disease 2019 (COVID-19); Sound pressure; Perception; Computer science; Audiology; Psychology; Physics; Medicine; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002590696,0.00009382202,0.0002067219,0.00001859006,0.0005765009,0.00001806757,0.002147104,0.00002510723,0.000009636402],"category_scores_gemma":[0.001178983,0.00003868774,0.0002583117,0.0005939192,0.0003026836,0.0001062011,0.0004992712,0.0006014099,2.344278e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001101066,"about_ca_system_score_gemma":0.0004008106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007499081,"about_ca_topic_score_gemma":3.871682e-7,"domain_scores_codex":[0.9977458,0.0004596496,0.0004014294,0.00008997663,0.001152322,0.0001508689],"domain_scores_gemma":[0.997393,0.0009870458,0.0008389807,0.0003904916,0.0003482232,0.00004228664],"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":[0.00006812164,0.00006283186,0.00000281227,0.00001918045,0.00006939272,1.674784e-7,0.004314806,0.935562,0.05380642,0.0001511013,0.0004858071,0.005457408],"study_design_scores_gemma":[0.000188479,0.0003323857,0.00003837554,0.00004876827,0.00007018401,0.00003006865,0.004826974,0.945566,0.02314279,0.02558618,0.000108431,0.00006135549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05479541,0.0001775212,0.9230527,0.02168595,0.00006912513,0.0001904567,0.000003894425,0.00000648788,0.00001844036],"genre_scores_gemma":[0.9835875,0.00007307264,0.01275969,0.003534378,0.00003032466,0.000004239803,3.236664e-8,0.000005542504,0.000005191199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9287921,"threshold_uncertainty_score":0.4434037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02654275229062256,"score_gpt":0.2662781607348221,"score_spread":0.2397354084441996,"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."}}