{"id":"W4221106069","doi":"10.1101/2022.03.10.22272238","title":"Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Nursing Research; York University; National Institutes of Health; Case Western Reserve University; American Heart Association; University of Washington; Tobacco-Related Disease Research Program; Johns Hopkins University; National Heart, Lung, and Blood Institute; Office of the President, University of California; University of California, Davis; University of Minnesota","keywords":"Nocturnal; Medicine; Cohort; Psychological intervention; Emergency medicine; Biomarker; Respiratory system; Polysomnography; Respiratory rate; Cohort study; Pediatrics; Internal medicine; Intensive care medicine; Heart rate; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005179186,0.0003190523,0.0003716096,0.0004009673,0.0001250463,0.00007477834,0.0004222385,0.0002092044,0.0003012486],"category_scores_gemma":[0.0001552914,0.0003920346,0.0001698247,0.0003654334,0.00004353921,0.0001829266,0.000451303,0.0008903702,0.00002496216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005562167,"about_ca_system_score_gemma":0.00007545271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006169279,"about_ca_topic_score_gemma":0.00001819826,"domain_scores_codex":[0.9983129,0.0001193105,0.0005534541,0.0003530418,0.0003203502,0.0003409435],"domain_scores_gemma":[0.9989622,0.0001180797,0.0002121777,0.0004770907,0.0001252322,0.0001052431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003080863,0.0001025348,0.5809684,0.002268288,0.0006301219,0.0001648875,0.001531561,0.1579269,0.2513258,0.0006523934,0.0004521348,0.003946152],"study_design_scores_gemma":[0.002363739,0.0006844488,0.2250045,0.003170334,0.0008121463,0.00002847716,0.001490451,0.02388139,0.6925917,0.04035315,0.003917206,0.005702536],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795744,0.0004807917,0.01043261,0.000008633425,0.003583822,0.0003645931,0.0002728631,0.0003106719,0.004971552],"genre_scores_gemma":[0.9980521,0.0001285384,0.0009146308,0.000009872375,0.0003690609,0.0001464168,0.0001703924,0.0001375566,0.00007147431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4412659,"threshold_uncertainty_score":0.9998531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02295777826165696,"score_gpt":0.2416007075076545,"score_spread":0.2186429292459975,"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."}}