{"id":"W2606389712","doi":"10.1109/bhi.2017.7897306","title":"Multimodal ambulatory sleep detection","year":2017,"lang":"en","type":"article","venue":"","topic":"Sleep and related disorders","field":"Psychology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Sleep & Circadian Network","funders":"National Institute of General Medical Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute on Aging","keywords":"Actigraphy; Sleep (system call); Offset (computer science); Wearable computer; Computer science; Artificial intelligence; Ambulatory; Speech recognition; Circadian rhythm; Medicine; Embedded system; 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":[0.0002373244,0.0005130647,0.0004269679,0.0005967307,0.0001051679,0.000324289,0.0003069431,0.0002738652,0.001998391],"category_scores_gemma":[0.001042332,0.0001012031,0.0003467099,0.0005081531,0.00005806519,0.0001997762,0.0003546378,0.0002118886,0.0005401099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001522505,"about_ca_system_score_gemma":0.0001881785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002200114,"about_ca_topic_score_gemma":0.003711223,"domain_scores_codex":[0.9997934,0.00002853092,0.00001494921,0.00007768358,0.0000610166,0.00002448807],"domain_scores_gemma":[0.9997808,0.00005113007,0.00004487469,0.00002283113,0.0000861559,0.0000141534],"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":[0.0008007513,0.0002912334,0.1204586,0.0004100237,0.000383465,0.0004208667,0.0001676245,0.00897213,0.121576,0.000639341,0.006503211,0.7393768],"study_design_scores_gemma":[0.0000810581,0.001022177,0.4764988,0.0001103086,0.0003293493,0.002280314,0.0002395848,0.4344477,0.07232796,0.001496613,0.01106209,0.0001040288],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7048146,0.001883041,0.2774945,0.0002231408,0.000202557,0.0003234339,0.004730316,0.002484826,0.007843597],"genre_scores_gemma":[0.9318552,0.0004197863,0.06221508,0.0001074936,0.00009116987,0.0001451678,0.001927139,0.00006728114,0.003171628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002200114,"threshold_uncertainty_score":0.006685317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434663259690729,"score_gpt":0.2964802473805798,"score_spread":0.2821336147836725,"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."}}