{"id":"W4378610836","doi":"10.1093/sleep/zsad077.0276","title":"0276 Detecting Apnea Hypopnea Index for Classified the Severity of Obstructive Sleep Apnea using PPG signals","year":2023,"lang":"en","type":"article","venue":"SLEEP","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canmore Museum and Geoscience Centre","funders":"","keywords":"Polysomnography; Obstructive sleep apnea; Wearable computer; Medicine; Sleep apnea; Sensitivity (control systems); Sleep (system call); Apnea–hypopnea index; Apnea; Computer science; Internal medicine; Embedded system; Engineering","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":[0.0008862966,0.0007811684,0.0004388432,0.001728448,0.0002014917,0.0008802598,0.0003471609,0.00046658,0.002721662],"category_scores_gemma":[0.002052675,0.0001587108,0.0005733141,0.0005277095,0.0001484204,0.0003715731,0.0003471281,0.0002553955,0.0009720696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002005168,"about_ca_system_score_gemma":0.0002941402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001559269,"about_ca_topic_score_gemma":0.002154699,"domain_scores_codex":[0.9993186,0.0002080797,0.00009522412,0.0001145772,0.0002161704,0.0000473119],"domain_scores_gemma":[0.9993148,0.0001811196,0.0001354691,0.00005572536,0.0002360423,0.0000768971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001046616,0.0003143096,0.8350828,0.0003101226,0.0004231955,0.0002430939,0.0001065718,0.003036685,0.01806432,0.0002657732,0.002647733,0.1384588],"study_design_scores_gemma":[0.0001157977,0.0009576578,0.9102797,0.0001062525,0.0003447128,0.001334933,0.0002234378,0.07038467,0.01211186,0.0005349734,0.003532873,0.00007309462],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9496595,0.002520329,0.0342155,0.0002379215,0.0002337326,0.0006394017,0.003476868,0.0008785572,0.008138211],"genre_scores_gemma":[0.9767582,0.0003508924,0.01941375,0.00007852716,0.00008396148,0.0002212255,0.001429299,0.00002723268,0.001636793],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002721662,"threshold_uncertainty_score":0.009104908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05938238898935162,"score_gpt":0.3318594093882823,"score_spread":0.2724770203989307,"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."}}