{"id":"W2922189800","doi":"10.5664/jcsm.7676","title":"Objective Relationship Between Sleep Apnea and Frequency of Snoring Assessed by Machine Learning","year":2019,"lang":"en","type":"article","venue":"Journal of Clinical Sleep Medicine","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Sleep & Circadian Network; Toronto General Hospital; University of Toronto; Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Medicine; Obstructive sleep apnea; Rehabilitation; Sleep apnea; Gerontology; Sleep medicine; Sleep disorder; Physical therapy; Psychiatry","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":[0.001606087,0.0005031065,0.0004214481,0.000999786,0.0002748097,0.0007011179,0.0002967708,0.0006194616,0.001564048],"category_scores_gemma":[0.006081248,0.0001554735,0.0003808714,0.0007700091,0.000215161,0.0006704482,0.0003772351,0.0005975979,0.0002879101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002313454,"about_ca_system_score_gemma":0.0002442943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001077301,"about_ca_topic_score_gemma":0.001938787,"domain_scores_codex":[0.999078,0.0002646489,0.0002025508,0.0001675416,0.0002256241,0.0000616213],"domain_scores_gemma":[0.9915446,0.004599543,0.002478804,0.0002367317,0.0007778162,0.0003626305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005012891,0.0001610552,0.9911097,0.00003193273,0.0002287718,0.0000217218,0.00002359704,0.0003334053,0.001083286,0.00001673426,0.00009629745,0.006392119],"study_design_scores_gemma":[0.00002194217,0.0006761974,0.9927424,0.000009442466,0.00008665856,0.0002382667,0.0000645912,0.005353086,0.0005900036,0.00006437548,0.0001441601,0.000008883379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951034,0.0006047997,0.001454549,0.00008444509,0.00003697572,0.0000383454,0.001214265,0.00004844951,0.001414761],"genre_scores_gemma":[0.9976444,0.0001736304,0.000884845,0.00003212317,0.00005456217,0.00002191437,0.0008465891,0.00000466729,0.0003371527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001606087,"threshold_uncertainty_score":0.0084939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07168449395205558,"score_gpt":0.4113015248051383,"score_spread":0.3396170308530828,"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."}}