{"id":"W3214734602","doi":"10.1016/j.csl.2021.101322","title":"Empirical Mode Decomposition articulation feature extraction on Parkinson’s Diadochokinesia","year":2021,"lang":"en","type":"article","venue":"Computer Speech & Language","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"H2020 Marie Skłodowska-Curie Actions; Horizon 2020; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Universidad de Antioquia","keywords":"Segmentation; Computer science; Artificial intelligence; Pattern recognition (psychology); Hilbert–Huang transform; Frame (networking); Feature (linguistics); Filter (signal processing); Speech recognition; Computer vision; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001845975,0.0003677827,0.0003185475,0.0008579788,0.0001684424,0.0002641182,0.0001073501,0.0002497625,0.001101518],"category_scores_gemma":[0.0004405769,0.00008523199,0.000421261,0.000508534,0.00007794116,0.0001520153,0.000218968,0.0002324795,0.0004646221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009476684,"about_ca_system_score_gemma":0.0001824826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0025904,"about_ca_topic_score_gemma":0.002793233,"domain_scores_codex":[0.9999182,0.00001457161,0.000009834544,0.00001735034,0.00002462389,0.00001525329],"domain_scores_gemma":[0.9998529,0.00005466142,0.00001299006,0.00001064707,0.00005584237,0.00001293453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001287496,0.00008714752,0.01975653,0.0002530585,0.00008541329,0.00139346,0.0001500258,0.007960692,0.2263393,0.0004830053,0.002008087,0.7401958],"study_design_scores_gemma":[0.00008961884,0.0006356954,0.3787028,0.0001197768,0.0003914061,0.004759328,0.0005777919,0.5131499,0.09150145,0.001143866,0.008843679,0.00008480006],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7733005,0.003511192,0.2183553,0.0002819581,0.0001838774,0.00007470984,0.001160868,0.0005490122,0.002582635],"genre_scores_gemma":[0.9675033,0.0008956683,0.02838072,0.00003332272,0.00005195282,0.0000214744,0.0007709129,0.0000427678,0.00229985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0025904,"threshold_uncertainty_score":0.005150676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01510550990543507,"score_gpt":0.377200725557779,"score_spread":0.3620952156523439,"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."}}