{"id":"W3183416950","doi":"10.1155/2021/6076828","title":"Improved Estimation of Parkinsonian Vowel Quality through Acoustic Feature Assimilation","year":2021,"lang":"en","type":"article","venue":"The Scientific World JOURNAL","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Vowel; Computer science; Speech recognition; Overfitting; Correlation; Cepstrum; Mel-frequency cepstrum; Linear regression; Regression analysis; Support vector machine; Pattern recognition (psychology); Artificial intelligence; Mathematics; Feature extraction; Artificial neural network; Machine learning","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":[0.001765172,0.00009807947,0.0002027294,0.00009871947,0.0004531693,0.0001723651,0.0001290798,0.00004542857,0.0003137842],"category_scores_gemma":[0.0005198236,0.00006383791,0.0001489985,0.000820855,0.000185595,0.0002147606,0.00003155359,0.000419362,0.00001389727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005951739,"about_ca_system_score_gemma":0.0003542231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001130564,"about_ca_topic_score_gemma":0.0003032918,"domain_scores_codex":[0.9985578,0.0001704466,0.0003412685,0.0001856635,0.0005334692,0.0002113467],"domain_scores_gemma":[0.998791,0.0001018455,0.0002722164,0.0003793449,0.0003839213,0.00007165464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006258275,0.001113307,0.007635428,0.000493222,0.0004916992,0.000121283,0.0160606,0.01024968,0.6411887,0.001158396,0.1626312,0.1582308],"study_design_scores_gemma":[0.01000216,0.0003447453,0.5444588,0.001907964,0.001838461,0.001914852,0.01174016,0.1519652,0.1802588,0.02646303,0.06807093,0.00103492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.893554,0.00221255,0.03563666,0.05718929,0.003625912,0.0004526268,0.00002540257,0.0000582059,0.007245339],"genre_scores_gemma":[0.9760675,0.00003992235,0.004210234,0.0004071378,0.0001620488,0.000001745124,0.000026712,0.000009810286,0.01907483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5368234,"threshold_uncertainty_score":0.3485457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0313298634776849,"score_gpt":0.3306924826512262,"score_spread":0.2993626191735413,"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."}}