{"id":"W2769893671","doi":"10.5539/cis.v11n1p8","title":"Pathological Voice Signal Analysis Using Machine Learning Based Approaches","year":2017,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Naive Bayes classifier; Bayes' theorem; SIGNAL (programming language); Artificial intelligence; Speech recognition; Pattern recognition (psychology); Machine learning; Support vector machine; Bayesian probability","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001468678,0.0008313199,0.0007981525,0.003238856,0.0004312513,0.001411704,0.0007789614,0.0009875054,0.001507665],"category_scores_gemma":[0.003771121,0.0002379457,0.0007947804,0.0009857692,0.0004537094,0.0008779688,0.000446546,0.0004996475,0.00106617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004666322,"about_ca_system_score_gemma":0.0005576587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002028081,"about_ca_topic_score_gemma":0.002243644,"domain_scores_codex":[0.9986346,0.0003588536,0.0001601717,0.0003248617,0.0004368485,0.00008464984],"domain_scores_gemma":[0.9983616,0.0007930305,0.0001953441,0.0001255232,0.0004897116,0.00003469051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002270111,0.0002824477,0.01331822,0.0003280656,0.0001819283,0.0003142263,0.0001256448,0.1107766,0.02157468,0.002470029,0.001737232,0.8486638],"study_design_scores_gemma":[0.00001162799,0.0001215344,0.006171322,0.00004565587,0.00003846979,0.0003417252,0.00007395021,0.9802402,0.007834949,0.003500519,0.00158532,0.00003474747],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05147275,0.001305599,0.9426103,0.0001679135,0.0001274828,0.0001923805,0.0002362886,0.001765885,0.002121319],"genre_scores_gemma":[0.5844101,0.0008978541,0.4114635,0.0001189448,0.0001342601,0.0002079221,0.000705039,0.00007339475,0.001989047],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003238856,"threshold_uncertainty_score":0.0077672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07345648068089958,"score_gpt":0.3018740718874626,"score_spread":0.228417591206563,"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."}}