{"id":"W4414793907","doi":"10.1093/sleepadvances/zpaf053.002","title":"O002 Machine learning applied to oximetry to detect paediatric sleep apnoea","year":2025,"lang":"en","type":"article","venue":"SLEEP Advances","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"Pulse oximetry; Predictive value; Gold standard (test); Tonsillectomy; Receiver operating characteristic; Patient data; Polysomnography; Predictive modelling","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004364744,0.0003535676,0.0005730765,0.001151127,0.0002527267,0.00005335465,0.0003831539,0.0001213706,0.0004360027],"category_scores_gemma":[0.00105243,0.0003223998,0.0001462956,0.00290433,0.000081003,0.0001374443,0.0004076992,0.0007040597,0.0008888152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002860747,"about_ca_system_score_gemma":0.00002975951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002934494,"about_ca_topic_score_gemma":0.00005735669,"domain_scores_codex":[0.9970549,0.0000949689,0.0004332369,0.0008300527,0.0007466155,0.0008401618],"domain_scores_gemma":[0.9983183,0.0003324464,0.00007853918,0.0005653889,0.0001984552,0.0005069287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008415616,0.0001035281,0.03737479,0.0002192417,0.0002061687,0.00004532947,0.0001725358,0.001883306,0.02571314,0.0005753221,0.0001552433,0.9327098],"study_design_scores_gemma":[0.01220893,0.003391959,0.09146087,0.0002432005,0.0009355792,0.00005887386,0.002287319,0.009870683,0.2601382,0.003149872,0.6139091,0.002345349],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6396414,0.02225423,0.2036547,0.006042652,0.00256069,0.00636745,0.00006261623,0.001257469,0.1181587],"genre_scores_gemma":[0.9785321,0.00006885711,0.01829238,0.001208683,0.0003522217,0.0002279088,0.00002169176,0.000060463,0.001235667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9303645,"threshold_uncertainty_score":0.9999228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008246391295973352,"score_gpt":0.2934234809778249,"score_spread":0.2851770896818515,"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."}}