{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005122577,0.00006149068,0.0001264665,0.0002471094,0.0006952238,0.0003371868,0.0001489495,0.00002756638,0.00001771845],"category_scores_gemma":[0.00007056292,0.00004509523,0.0000435628,0.0002806533,0.0002928519,0.002259313,0.00009285932,0.0000996282,0.000009598243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001341385,"about_ca_system_score_gemma":0.00005673769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001703447,"about_ca_topic_score_gemma":0.000001092328,"domain_scores_codex":[0.9993576,0.00001064271,0.0001422687,0.0001098171,0.0002492468,0.0001304719],"domain_scores_gemma":[0.9995263,0.00001636169,0.0001089587,0.0001760382,0.00008627252,0.00008605753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006693062,0.00008430027,0.7671843,0.00009510275,0.00006854555,0.000009622392,0.002520347,0.03033117,0.001002438,0.000691015,0.00003039362,0.1979159],"study_design_scores_gemma":[0.0002594147,0.00005365212,0.2108202,0.000006545475,0.00004199017,0.000008204473,0.00005094827,0.788,0.0001275993,0.000005414753,0.000577757,0.00004820648],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.546104,0.00001493125,0.4513828,0.0002851394,0.00003128586,0.00006684335,0.000001092821,0.00002375109,0.002090238],"genre_scores_gemma":[0.9827883,0.000005949898,0.01652222,0.0006388722,0.00002336235,9.019699e-7,0.00001046482,9.936633e-7,0.000008961448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7576689,"threshold_uncertainty_score":0.534717,"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."}}