{"id":"W4386713054","doi":"10.3390/info14090502","title":"PDD-ET: Parkinson’s Disease Detection Using ML Ensemble Techniques and Customized Big Dataset","year":2023,"lang":"en","type":"article","venue":"Information","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Artificial intelligence; Boosting (machine learning); Deep learning; Parkinson's disease; Computer science; Decision tree; Machine learning; Movement assessment; Support vector machine; Population; Disease; Medicine; Psychology; Neuroscience; Internal medicine","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":[0.0001771566,0.00007112364,0.00009235113,0.0002328168,0.00007525482,0.00004147329,0.00002351443,0.00004583184,0.000007477691],"category_scores_gemma":[0.00007009444,0.00006403231,0.00002224772,0.0002183564,0.00001715004,0.0009626053,0.00002575692,0.00007128046,0.00007735797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000249293,"about_ca_system_score_gemma":0.00004150409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000497869,"about_ca_topic_score_gemma":0.0000103434,"domain_scores_codex":[0.9995174,0.00001589312,0.0001543524,0.00006521092,0.0001353963,0.0001117514],"domain_scores_gemma":[0.9996794,0.00001771556,0.00006300774,0.0001375169,0.00002726615,0.00007502261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001544047,0.0000569831,0.005366409,0.0006677688,0.00006117435,0.00003897526,0.001502339,0.000130847,0.01267781,0.0001729807,0.01616523,0.9616154],"study_design_scores_gemma":[0.002452694,0.00009168845,0.01490445,0.0001269043,0.000110754,0.00004763936,0.0007332997,0.02975669,0.01097,0.0001913441,0.9404144,0.0002001158],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915352,0.00005027493,0.004698097,0.001389974,0.0001535199,0.0005687469,0.0001637837,0.0004141103,0.001026299],"genre_scores_gemma":[0.9949953,0.0003756448,0.0006802592,0.001114113,0.00007079683,0.00003381494,0.002654874,0.000009341659,0.00006587913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9614154,"threshold_uncertainty_score":0.2611162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02933549246099595,"score_gpt":0.3049314146727496,"score_spread":0.2755959222117537,"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."}}