{"id":"W2160433250","doi":"10.1213/ane.0000000000000222","title":"Improving Pulse Oximetry Pitch Perception with Multisensory Perceptual Training","year":2014,"lang":"en","type":"article","venue":"Anesthesia & Analgesia","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute on Deafness and Other Communication Disorders","keywords":"Pulse oximetry; Medicine; Anesthesiology; Pulse (music); Perception; Anesthesia; Interval training; Confidence interval; Audiology; Millisecond; Oxygen saturation; Internal medicine; Oxygen; Computer science; Neuroscience; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003812133,0.0002542504,0.0004048797,0.0002548809,0.0002330779,0.00001819943,0.000117356,0.0003131993,0.0002045992],"category_scores_gemma":[0.00007506468,0.0002124705,0.00008939851,0.0002963224,0.0002144507,0.0001296444,0.00001308085,0.0005242978,0.0002519776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009679651,"about_ca_system_score_gemma":0.00008091398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004059798,"about_ca_topic_score_gemma":0.00002306058,"domain_scores_codex":[0.9983177,0.0001217146,0.0003010966,0.0004472695,0.0003055339,0.0005067243],"domain_scores_gemma":[0.9990268,0.00008686294,0.0001128212,0.0004351606,0.0001089043,0.0002294089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004029309,0.0001615884,0.3695673,0.0002430657,0.00006750489,0.0004066559,0.004094993,0.00001444327,0.01735572,0.0004579138,0.0001545159,0.6070734],"study_design_scores_gemma":[0.002172326,0.002504568,0.9715627,0.0003600734,0.0002279092,0.003164389,0.009835662,0.004970544,0.001644203,0.00002240467,0.002928375,0.0006068466],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941155,0.00007175596,0.002392575,0.001842177,0.00004827726,0.0002916506,2.998869e-7,0.0003243036,0.0009134357],"genre_scores_gemma":[0.9913765,0.00001652921,0.006817585,0.0008964356,0.0003583111,0.00002404854,0.00002178368,0.00005325954,0.0004355233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6064665,"threshold_uncertainty_score":0.8664296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693653774107466,"score_gpt":0.2689179796296147,"score_spread":0.24198144188854,"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."}}