{"id":"W1918109950","doi":"10.1097/aln.0000000000000692","title":"Identifying Obstructive Sleep Apnea in Administrative Data","year":2015,"lang":"en","type":"article","venue":"Anesthesiology","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Ottawa; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Ottawa Hospital Anesthesia Alternate Funds Association; University of Toronto; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Medicine; Polysomnogram; Obstructive sleep apnea; Diagnosis code; Continuous positive airway pressure; Sleep apnea; Sleep study; Apnea–hypopnea index; Polysomnography; Intensive care medicine; Emergency medicine; Internal medicine; Apnea; Population","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000599683,0.000179312,0.0004354508,0.0002467777,0.00003911869,0.0000161358,0.000468013,0.0001841116,0.00009718729],"category_scores_gemma":[0.001068146,0.0001575675,0.00003762405,0.0003761789,0.0003598949,0.0002434867,0.0003082014,0.0004315066,0.0002971473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468524,"about_ca_system_score_gemma":0.0001491649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001561425,"about_ca_topic_score_gemma":0.00008164582,"domain_scores_codex":[0.9979956,0.0002799295,0.0003214747,0.0006316375,0.0002998208,0.0004715064],"domain_scores_gemma":[0.9982829,0.0002366892,0.00008304737,0.0009425524,0.0001848318,0.0002699498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001194124,0.0002841594,0.9492807,0.00005101073,0.0001357227,0.003303877,0.002493169,0.000005152236,0.002633231,0.002269052,0.0003851732,0.03796463],"study_design_scores_gemma":[0.002843032,0.0009787166,0.9776505,0.00002410248,0.00005146245,0.001335387,0.006465521,0.001459221,0.002315123,0.003922566,0.002701266,0.0002530657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949245,0.0003782191,0.0001354079,0.0004841437,0.0001640019,0.0004275249,0.00001176222,0.00004861924,0.003425803],"genre_scores_gemma":[0.9963307,0.000006772089,0.002938434,0.0002485837,0.000149402,0.00002960314,0.0001590155,0.00002666255,0.0001107785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03771156,"threshold_uncertainty_score":0.6425418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1951593681276263,"score_gpt":0.4037132495477268,"score_spread":0.2085538814201005,"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."}}