{"id":"W4403450759","doi":"10.1371/journal.pone.0309612","title":"Speaking to a metronome reduces kinematic variability in typical speakers and people who stutter","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Stuttering Research and Treatment","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; Economic and Social Research Council; Bundesministerium für Bildung und Forschung; European Commission; Wellcome Trust; Royal Academy of Engineering; National Institute for Health and Care Research; Australian Government; Department of Health and Social Care","keywords":"Metronome; Audiology; Stuttering; Fluency; Psychology; Phonation; Vocal tract; Speech production; Medicine; Speech recognition; Rhythm; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004421297,0.0001079199,0.0002531196,0.0001794444,0.00002498516,0.00007002369,0.00008620368,0.00003999621,0.00124661],"category_scores_gemma":[0.0001776754,0.00009107555,0.00002765789,0.00028497,0.00003185649,0.00003894768,0.00008793625,0.0001555741,0.0005492008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001058837,"about_ca_system_score_gemma":0.00001855757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002792711,"about_ca_topic_score_gemma":0.0001494925,"domain_scores_codex":[0.9988119,0.0001295529,0.0001757601,0.000382133,0.0001801473,0.000320513],"domain_scores_gemma":[0.9992653,0.0003562834,0.00001109163,0.0002339696,0.0000144098,0.0001189095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001446402,0.01210065,0.8075895,0.002480946,0.0048423,0.001074255,0.0800772,0.00001291801,0.01909496,0.007620255,0.00257973,0.06108092],"study_design_scores_gemma":[0.0005183279,0.0003225575,0.9957737,0.0004847831,0.00008609913,0.000006402007,0.0006298973,0.0002691931,0.000791948,0.0008112517,0.0001322485,0.0001736154],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920237,0.0002866344,0.00005684542,0.002769337,0.00006850983,0.0004236505,0.000008147174,0.00005178008,0.004311386],"genre_scores_gemma":[0.9976556,0.000004900422,0.001439965,0.00008181552,0.00009670171,0.0001505415,0.00000239836,0.00001583977,0.0005522024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1881842,"threshold_uncertainty_score":0.9996664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05832246578462758,"score_gpt":0.3286908951933472,"score_spread":0.2703684294087196,"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."}}