{"id":"W3005609949","doi":"10.1093/sleep/zsaa004","title":"Predicting sleep apnea responses to oral appliance therapy using polysomnographic airflow","year":2020,"lang":"en","type":"article","venue":"SLEEP","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Sleep & Circadian Network","funders":"National Institutes of Health; National Heart Foundation of Australia; Fundação de Amparo à Pesquisa do Estado de São Paulo; American Heart Association","keywords":"Oral appliance; Medicine; Obstructive sleep apnea; Apnea; Polysomnography; Airflow; Sleep apnea; Body mass index; Airway; Anesthesia; Cardiology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003749748,0.000315715,0.0004805137,0.0003151913,0.0002322564,0.00006602947,0.0003261731,0.0001388565,0.0002984501],"category_scores_gemma":[0.0005083862,0.0002913334,0.0002007128,0.001606527,0.0001717702,0.0001759062,0.0001905919,0.0005498491,0.0002101177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001142762,"about_ca_system_score_gemma":0.00005070504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008058042,"about_ca_topic_score_gemma":0.000007432396,"domain_scores_codex":[0.9970647,0.0001796032,0.0003980376,0.0007230203,0.0008580511,0.0007766309],"domain_scores_gemma":[0.9982803,0.0001078652,0.00009080402,0.0005314637,0.0002282165,0.0007613151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005014552,0.0002276188,0.5856482,0.000114005,0.0003369826,0.0002365401,0.002092826,0.0002491854,0.2519328,0.0000914215,0.0001174001,0.1539384],"study_design_scores_gemma":[0.01848262,0.006464284,0.3863243,0.000266365,0.0004638636,0.0003423489,0.004430349,0.3834824,0.1760792,0.0002230902,0.02127228,0.002168912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841961,0.0007335792,0.007873519,0.004793927,0.0002419993,0.001211634,0.00002971612,0.0002930062,0.000626565],"genre_scores_gemma":[0.9882932,0.00001430757,0.007908537,0.002902815,0.0006603911,0.00005824531,0.00001121985,0.0000935616,0.00005770849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3832332,"threshold_uncertainty_score":0.9999539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0644393594553797,"score_gpt":0.3366970163133809,"score_spread":0.2722576568580012,"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."}}