{"id":"W4410004216","doi":"10.3390/biomedinformatics5020023","title":"Escalate Prognosis of Parkinson’s Disease Employing Wavelet Features and Artificial Intelligence from Vowel Phonation","year":2025,"lang":"en","type":"article","venue":"BioMedInformatics","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Phonation; Vowel; Wavelet; Speech recognition; Parkinson's disease; Audiology; Artificial intelligence; Disease; Medicine; Computer science; Pathology","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":[0.0001164576,0.0001125113,0.0002011317,0.0002261762,0.00005507827,0.0000295691,0.00007063828,0.00007720191,0.00002262986],"category_scores_gemma":[0.0002249484,0.00009385859,0.00005359554,0.0003018221,0.0001093008,0.0001492416,0.00004896549,0.00009637772,0.000007631088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002605335,"about_ca_system_score_gemma":0.00008959899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005489321,"about_ca_topic_score_gemma":0.0000176623,"domain_scores_codex":[0.9991022,0.000008351918,0.0004018235,0.0001027477,0.0002378394,0.000147047],"domain_scores_gemma":[0.9994681,0.00007637987,0.0001070074,0.000150001,0.00009052764,0.0001079814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005253174,0.0004017123,0.06007759,0.001667421,0.0002721777,0.00001171308,0.00855695,0.000006599721,0.002017329,0.002131543,0.007002012,0.9173296],"study_design_scores_gemma":[0.001102673,0.0002748158,0.8790646,0.001565572,0.0007504374,0.000006122798,0.007330699,0.03680735,0.03796382,0.01943065,0.0152211,0.0004821184],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845784,0.0006188867,0.008167472,0.00474645,0.0002967365,0.0005615664,0.00008505611,0.00007084417,0.0008745538],"genre_scores_gemma":[0.9933367,0.00035424,0.005505713,0.0005123168,0.00004196672,0.00001646437,0.0001315328,0.00000668986,0.00009440469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9168475,"threshold_uncertainty_score":0.3827443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078635403857738,"score_gpt":0.2876705030184873,"score_spread":0.26688414897991,"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."}}