{"id":"W3196259627","doi":"10.2196/29200","title":"Predicting Prolonged Apnea During Nurse-Administered Procedural Sedation: Machine Learning Study","year":2021,"lang":"en","type":"article","venue":"JMIR Perioperative Medicine","topic":"Anesthesia and Sedative Agents","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto","funders":"National Health and Medical Research Council; Medical Research Council; University of Toronto","keywords":"Capnography; Medicine; ALARM; Apnea; Sedation; Logistic regression; Sleep apnea; Breathing; Emergency medicine; Anesthesia; Internal medicine; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003460825,0.0004195771,0.0008346175,0.0001523672,0.0005719456,0.00004526774,0.00012505,0.0001051458,0.001604583],"category_scores_gemma":[0.0008112161,0.0003093225,0.00009504618,0.0005768207,0.0002331594,0.0002239906,0.00006350201,0.0007216865,0.00005853665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001330179,"about_ca_system_score_gemma":0.0002568967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000289872,"about_ca_topic_score_gemma":0.00007939375,"domain_scores_codex":[0.9970512,0.0004081627,0.000647936,0.0007510618,0.0006988831,0.0004426959],"domain_scores_gemma":[0.9984822,0.00008713008,0.0001918683,0.0003853307,0.0005575027,0.0002959846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007604089,0.0008820489,0.9083875,0.0002250965,0.0002362216,0.001965404,0.04920782,0.000009447244,0.03754756,0.0000337944,0.00007544914,0.0006692056],"study_design_scores_gemma":[0.01205487,0.004998087,0.8949038,0.0005231639,0.0002905796,0.001459515,0.07262294,0.00344274,0.006047029,0.000001652124,0.003250193,0.0004054401],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854749,0.0003344551,0.00004757892,0.006073405,0.0001438174,0.002075232,0.000003893324,0.0002096041,0.005637048],"genre_scores_gemma":[0.9653868,0.0000142903,0.0001795864,0.000828232,0.0007108086,0.0004183406,0.0001999189,0.00006361378,0.03219841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03150053,"threshold_uncertainty_score":0.9999359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02908346991438,"score_gpt":0.3232960388294018,"score_spread":0.2942125689150218,"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."}}