{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001640445,0.002049644,0.001137198,0.002217293,0.0005421398,0.0008621513,0.001645461,0.001402246,0.0009765164],"category_scores_gemma":[0.002461213,0.0003307384,0.001668229,0.001142257,0.0002535562,0.001323477,0.001489325,0.00141695,0.0007434028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007025821,"about_ca_system_score_gemma":0.0007568132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01182123,"about_ca_topic_score_gemma":0.01951084,"domain_scores_codex":[0.9991443,0.0002053707,0.00008471761,0.0002919764,0.0001588963,0.0001147475],"domain_scores_gemma":[0.9991174,0.0002345696,0.00008000846,0.0002748413,0.0002083032,0.00008485173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001081273,0.001520118,0.0865364,0.000562366,0.001861673,0.001328326,0.000168906,0.2738205,0.008790168,0.001783247,0.1082215,0.5143255],"study_design_scores_gemma":[0.00007354475,0.0002691379,0.01556368,0.00005176212,0.0001864771,0.0004311715,0.00008798244,0.9671833,0.004651005,0.002259773,0.009177931,0.00006438744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6000971,0.007927402,0.2730169,0.002975223,0.001808203,0.0006867088,0.07564887,0.03042249,0.007417095],"genre_scores_gemma":[0.7334976,0.001010236,0.120973,0.0007246164,0.0003528563,0.0003769923,0.1390741,0.0002825748,0.003707997],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01182123,"threshold_uncertainty_score":0.02350485,"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."}}