{"id":"W2609716146","doi":"10.1093/sleepj/zsx050.068","title":"0069 DEVELOPMENT AND VALIDATION OF AN ALGORITHM FOR THE STUDY OF SLEEP USING A BIOMETRIC SHIRT IN YOUNG HEALTHY ADULTS","year":2017,"lang":"en","type":"article","venue":"SLEEP","topic":"Sleep and related disorders","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Hôpital Rivière-des-Prairies; Carré Technologies (Canada)","funders":"","keywords":"Polysomnography; Heart rate; Non-rapid eye movement sleep; Audiology; Medicine; Sleep (system call); Respiratory rate; Sleep medicine; Sleep onset; Algorithm; Eye movement; Psychology; Speech recognition; Apnea; Computer science; Anesthesia; Insomnia; Sleep disorder; Internal medicine; Psychiatry; Blood pressure; Ophthalmology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00435349,0.0007914123,0.0007996366,0.001764838,0.0004461654,0.001177669,0.0009038859,0.001133415,0.001847316],"category_scores_gemma":[0.009753714,0.0003432723,0.000587802,0.0006003647,0.0002589982,0.000610167,0.0008179441,0.0004946671,0.001651385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003640229,"about_ca_system_score_gemma":0.0009120374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002277614,"about_ca_topic_score_gemma":0.002360224,"domain_scores_codex":[0.9976097,0.0007163662,0.000301273,0.0006429339,0.0006339846,0.00009568808],"domain_scores_gemma":[0.9955969,0.001595849,0.000300935,0.000218788,0.002149239,0.0001382355],"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":[0.001497664,0.0004712217,0.1417374,0.0002712644,0.0002683878,0.0003429506,0.0004412367,0.0124398,0.04251436,0.0007638404,0.003181095,0.7960708],"study_design_scores_gemma":[0.000400915,0.001646428,0.1574416,0.0001531401,0.0001898488,0.001751384,0.0003186859,0.8033541,0.0264244,0.001080144,0.007130754,0.0001085531],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2815434,0.0005008133,0.7099124,0.0001609666,0.0001503675,0.0009691951,0.0005891363,0.004189258,0.001984474],"genre_scores_gemma":[0.3609873,0.0001592163,0.6348095,0.00008572375,0.00003241856,0.0008779832,0.0007876517,0.0001467826,0.002113471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00435349,"threshold_uncertainty_score":0.02302372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04078028043863485,"score_gpt":0.3505906302410934,"score_spread":0.3098103498024585,"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."}}