{"id":"W4379376807","doi":"10.2147/nss.s397196","title":"Sleep Apnea Detection by Tracheal Motion and Sound, and Oximetry via Application of Deep Neural Networks","year":2023,"lang":"en","type":"article","venue":"Nature and Science of Sleep","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University Health Network; Toronto Rehabilitation Institute; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Polysomnography; Apnea; Sleep apnea; Breathing; Sleep (system call); Audiology; Anesthesia; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005228499,0.0005815584,0.0003508354,0.0004736245,0.0001511937,0.0003589078,0.0003743293,0.0003580239,0.0004839266],"category_scores_gemma":[0.001270745,0.0002232518,0.0003680882,0.0003046232,0.0001294434,0.0003298627,0.0005811789,0.0005422958,0.0001480656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003574893,"about_ca_system_score_gemma":0.0004853808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006906579,"about_ca_topic_score_gemma":0.008449437,"domain_scores_codex":[0.9998311,0.00004859477,0.0000150935,0.00004417976,0.00003216722,0.00002881658],"domain_scores_gemma":[0.9997507,0.0001179419,0.00003845518,0.00001418462,0.00006281784,0.00001586626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005828096,0.0008132357,0.05101021,0.0002210301,0.0003174307,0.0003014559,0.0001781885,0.2693257,0.02180961,0.0008135592,0.002842312,0.6517844],"study_design_scores_gemma":[0.00000752319,0.00008260887,0.005449639,0.00001344201,0.00002266217,0.00002839133,0.00001773078,0.9925127,0.001340751,0.00034362,0.0001748815,0.000006098895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6059958,0.001820309,0.3872883,0.0005059651,0.0001282127,0.0001482058,0.0004029859,0.0008877725,0.002822362],"genre_scores_gemma":[0.9593868,0.0004041066,0.03845015,0.0000946928,0.00003405071,0.00008798271,0.0003584723,0.00001089564,0.00117273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006906579,"threshold_uncertainty_score":0.01373273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007262029834826355,"score_gpt":0.2792460778697038,"score_spread":0.2719840480348775,"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."}}