{"id":"W2069929513","doi":"10.1017/s0025100313000327","title":"A study of laryngeal gestures in Mandarin citation tones using simultaneous laryngoscopy and laryngeal ultrasound (SLLUS)","year":2014,"lang":"en","type":"article","venue":"Journal of the International Phonetic Association","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Larynx; Laryngoscopy; Tone (literature); Mandarin Chinese; Articulatory phonetics; Audiology; Speech production; Vocal folds; Phonation; Medicine; Acoustics; Speech recognition; Computer science; Anatomy; Surgery; Intubation; Linguistics; Physics","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":[0.001144075,0.00008851007,0.0001993267,0.0002129929,0.00006077018,0.0001074007,0.0004576521,0.00006057653,0.000008935687],"category_scores_gemma":[0.00168701,0.00006902264,0.00006552876,0.0001989839,0.0000160817,0.0002857661,0.00008230315,0.0001775581,0.000001165069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002267374,"about_ca_system_score_gemma":0.00004871758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001244328,"about_ca_topic_score_gemma":0.0002389757,"domain_scores_codex":[0.9982715,0.0002536857,0.0004871768,0.0001206626,0.0007622715,0.0001046779],"domain_scores_gemma":[0.9975862,0.001094513,0.0008340065,0.0001086615,0.0003437951,0.00003282031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003579479,0.003151104,0.8357183,0.00004694215,0.0008042554,0.00007401712,0.02399069,0.01459573,0.05750107,0.001343531,0.0009567815,0.0614596],"study_design_scores_gemma":[0.004256809,0.0006052983,0.873813,0.0002130859,0.0001043994,0.0002553556,0.001579288,0.09917524,0.01006006,0.009347717,0.0003252003,0.000264524],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941803,0.00003096984,0.003987364,0.0007347778,0.0006998705,0.0001165485,0.000002462364,0.000006167547,0.0002415753],"genre_scores_gemma":[0.9950122,0.00002100495,0.004632063,0.0001356902,0.0001183454,0.000001342209,5.557488e-7,0.000005483845,0.00007327078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08457951,"threshold_uncertainty_score":0.2814662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320693738831537,"score_gpt":0.2537196381902821,"score_spread":0.2405127008019667,"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."}}