{"id":"W2951997252","doi":"10.1093/sleep/zsz117","title":"Actigraphic detection of periodic limb movements: development and validation of a potential device-independent algorithm. A proof of concept study","year":2019,"lang":"en","type":"article","venue":"SLEEP","topic":"Restless Legs Syndrome Research","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Health Sciences Centre; Toronto Metropolitan University","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Proof of concept; Algorithm; Computer science; Actigraphy; Physical medicine and rehabilitation; Artificial intelligence; Computer vision; Psychology; Medicine; Neuroscience; Circadian rhythm","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":[0.004434681,0.0009969757,0.0006875028,0.0005525253,0.0002521588,0.001026892,0.001338194,0.001550829,0.001413597],"category_scores_gemma":[0.006047049,0.0004035346,0.0004792897,0.0002573993,0.0004915433,0.0008398175,0.0005011002,0.0009041236,0.0008052065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003487479,"about_ca_system_score_gemma":0.0007192039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000541804,"about_ca_topic_score_gemma":0.0005490237,"domain_scores_codex":[0.9982255,0.0004852648,0.00009552277,0.0003380948,0.0007935832,0.00006201048],"domain_scores_gemma":[0.997554,0.0008839224,0.000301865,0.000216137,0.0009291687,0.0001149266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002669372,0.001612875,0.011663,0.00102881,0.0003718303,0.000518869,0.0001437164,0.009930436,0.6236523,0.001858556,0.003341049,0.3432094],"study_design_scores_gemma":[0.001600127,0.01317108,0.0259671,0.0001329349,0.0003834563,0.003465916,0.00009861055,0.4321623,0.5066065,0.000927956,0.01530911,0.0001749067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1285248,0.001167545,0.8645616,0.000485295,0.0004203283,0.001962538,0.0002866544,0.001281376,0.001309824],"genre_scores_gemma":[0.316461,0.0005501133,0.6776613,0.0005204415,0.0001794005,0.001926553,0.0003768892,0.00009883816,0.002225495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004434681,"threshold_uncertainty_score":0.02345306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01946974831396749,"score_gpt":0.2923947878555383,"score_spread":0.2729250395415708,"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."}}