{"id":"W4401824487","doi":"10.1002/mds.29987","title":"Automated Sleep Detection in Movement Disorders Using Deep Brain Stimulation and Machine Learning","year":2024,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; Krembil Foundation; University of Toronto","funders":"Genome Alberta; Genome British Columbia; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Ontario Genomics Institute; Boston Scientific Corporation","keywords":"Deep brain stimulation; Movement disorders; Sleep (system call); Neuroscience; Physical medicine and rehabilitation; Movement (music); Psychology; Stimulation; Medicine; Artificial intelligence; Computer science; Parkinson's disease; Internal medicine","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":[0.0005315262,0.0004375995,0.0002440648,0.0004147696,0.00008756602,0.0003791884,0.0002295039,0.0003556186,0.0007998043],"category_scores_gemma":[0.0007807026,0.0001167101,0.0002545697,0.0002046881,0.0002219349,0.0002890619,0.0002612197,0.0003080575,0.0002080887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003168133,"about_ca_system_score_gemma":0.0002826823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001044198,"about_ca_topic_score_gemma":0.002141089,"domain_scores_codex":[0.9998559,0.00004628339,0.00001031442,0.00003119868,0.00004059254,0.00001563547],"domain_scores_gemma":[0.999773,0.0001191012,0.00004050619,0.00001288541,0.00004187801,0.00001265521],"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":[0.001179318,0.0006130462,0.02855711,0.00058193,0.0003674284,0.0003358151,0.000117574,0.07531181,0.1727281,0.001308621,0.002506264,0.716393],"study_design_scores_gemma":[0.0001556253,0.001560513,0.04368714,0.0001040844,0.0001141051,0.0004914543,0.00006198346,0.9048074,0.04327111,0.003343559,0.002353819,0.00004916706],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5726404,0.005040926,0.4140174,0.0009159981,0.0001574688,0.0003639864,0.000729707,0.001605446,0.004528722],"genre_scores_gemma":[0.9311324,0.0007918957,0.06662195,0.000182747,0.00004929385,0.0001644334,0.0002685685,0.00002587698,0.0007628525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001044198,"threshold_uncertainty_score":0.002811015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340233617360116,"score_gpt":0.2709826510332841,"score_spread":0.2575803148596829,"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."}}