{"id":"W4403292673","doi":"10.1016/j.bspc.2024.106854","title":"Derivation and validation of heart rate variability based Machine learning prognostic models for patients with suspected sepsis","year":2024,"lang":"en","type":"article","venue":"Biomedical Signal Processing and Control","topic":"Heart Rate Variability and Autonomic Control","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Ottawa Hospital","funders":"","keywords":"Sepsis; Computer science; Machine learning; Medicine; Artificial intelligence; Intensive care medicine; Internal medicine","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":[0.003145819,0.0006242257,0.0007223099,0.0007104946,0.0002802337,0.001122609,0.0006045189,0.0007878743,0.0007198742],"category_scores_gemma":[0.009619387,0.0002654031,0.0005170405,0.0003327936,0.0001971002,0.0004493441,0.0005193764,0.001160345,0.0004913599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003919487,"about_ca_system_score_gemma":0.0009869505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002545965,"about_ca_topic_score_gemma":0.001587217,"domain_scores_codex":[0.9994837,0.0001927955,0.00006405789,0.0001010671,0.00009964,0.00005870978],"domain_scores_gemma":[0.9963576,0.002394599,0.0002490619,0.0002133705,0.0006910501,0.00009432468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001580526,0.0008800077,0.2477686,0.0001698471,0.0005863219,0.0004315164,0.0002258049,0.4508769,0.01089229,0.001136231,0.003390178,0.2820618],"study_design_scores_gemma":[0.0000199283,0.0001604226,0.01622156,0.00002329352,0.00005184891,0.0000754003,0.00002187953,0.9810721,0.001781792,0.0003613431,0.0001997238,0.00001070303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7710921,0.0007821351,0.2240946,0.0006143209,0.000158476,0.0001703566,0.00108094,0.0007813,0.001225775],"genre_scores_gemma":[0.9865681,0.00009625926,0.01227872,0.00003655478,0.00001809455,0.00005844787,0.0007380556,0.00001484231,0.0001910064],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003145819,"threshold_uncertainty_score":0.01663685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031880111497652,"score_gpt":0.238899785188268,"score_spread":0.2285809840732914,"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."}}