{"id":"W4238884758","doi":"10.2196/preprints.26524","title":"Noncontact Sleep Monitoring With Infrared Video Data to Estimate Sleep Apnea Severity and Distinguish Between Positional and Nonpositional Sleep Apnea: Model Development and Experimental Validation (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Supine position; Sleep apnea; Apnea; Polysomnography; Medicine; Sleep (system call); Central sleep apnea; 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":[0.0008355973,0.0006910168,0.000398889,0.0004969098,0.0001488576,0.0004858799,0.0006222785,0.0005644487,0.00187642],"category_scores_gemma":[0.001515643,0.0001690798,0.000803485,0.000289684,0.0001468904,0.000298882,0.0003647893,0.0004965069,0.0005935359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004834178,"about_ca_system_score_gemma":0.0004311878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01598372,"about_ca_topic_score_gemma":0.01113331,"domain_scores_codex":[0.9997453,0.00005364085,0.00001894412,0.00007336073,0.00007707564,0.00003157698],"domain_scores_gemma":[0.9994234,0.0002541619,0.00005449931,0.00005141754,0.0001981311,0.00001846771],"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":[0.001108002,0.001123748,0.03516231,0.000520057,0.0004226949,0.0002435051,0.0001334449,0.4560529,0.03364705,0.0007144513,0.004286737,0.4665851],"study_design_scores_gemma":[0.000009187553,0.0001479897,0.006673966,0.00001538602,0.00002374309,0.00002448932,0.00001550516,0.9874312,0.005302796,0.00008011574,0.0002674714,0.000008200722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6250327,0.001837883,0.3638139,0.0003733516,0.0004945953,0.0004830313,0.001886339,0.002241606,0.003836587],"genre_scores_gemma":[0.9301291,0.0004777195,0.06272444,0.00009710535,0.00005074836,0.0003925817,0.002163391,0.00005563786,0.003909237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01598372,"threshold_uncertainty_score":0.03178138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06244281502566583,"score_gpt":0.3537259195949641,"score_spread":0.2912831045692982,"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."}}