{"id":"W4409180738","doi":"10.1038/s41598-025-96575-6","title":"Explainable artificial intelligence to diagnose early Parkinson’s disease via voice analysis","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Parkinson's disease; Disease; Computer science; Speech recognition; Medicine; Data 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":[0.001073908,0.0001892092,0.0003669495,0.001028018,0.0003761163,0.0002971474,0.0001582284,0.00006500164,0.0003732721],"category_scores_gemma":[0.000847773,0.0001739788,0.0003101586,0.004507231,0.0001617528,0.0001782895,0.0001031418,0.0001426745,0.0002212564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001023588,"about_ca_system_score_gemma":0.000346177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003620869,"about_ca_topic_score_gemma":0.0004755383,"domain_scores_codex":[0.9971052,0.00004151492,0.0006441565,0.00107427,0.0006534696,0.0004813637],"domain_scores_gemma":[0.9975919,0.00006122011,0.0001339624,0.001396628,0.0003155923,0.0005007662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00047143,0.001797796,0.8275336,0.0003152277,0.001076821,0.008735294,0.002054107,0.00201678,0.00727953,0.001262426,0.05704595,0.09041103],"study_design_scores_gemma":[0.0001887109,0.0002244624,0.2793715,0.0004497088,0.004574152,0.00004975254,0.002047762,0.004014095,0.05037084,0.08528467,0.572401,0.001023317],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9607931,0.0003534608,0.02873997,0.004008607,0.002717563,0.0007737563,0.000003208242,0.0001345132,0.002475865],"genre_scores_gemma":[0.9826667,0.000008834464,0.0006156155,0.0007205557,0.00006423998,0.0001069483,0.00006176314,0.00001227496,0.01574312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5481622,"threshold_uncertainty_score":0.7094648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677620555982128,"score_gpt":0.2986616591160872,"score_spread":0.2818854535562659,"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."}}