{"id":"W4401715495","doi":"10.1002/ehf2.15027","title":"Unsupervised Machine Learning to Identify Subphenotypes Among Cardiac Intensive Care Unit Patients with Heart Failure","year":2024,"lang":"en","type":"article","venue":"ESC Heart Failure","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Medicine; Heart failure; Coronary care unit; Intensive care unit; Intensive care medicine; Cohort; Population; Intensive care; Internal medicine; Myocardial infarction","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":[0.001466544,0.0002490871,0.0003448415,0.001583355,0.0004002025,0.0005753784,0.0004487896,0.0003699802,0.001043046],"category_scores_gemma":[0.006977949,0.0001200538,0.0004383315,0.0007652708,0.0003439078,0.0003452264,0.0006725316,0.0004436727,0.0002383485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003111796,"about_ca_system_score_gemma":0.0005622765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00254209,"about_ca_topic_score_gemma":0.00334527,"domain_scores_codex":[0.9990807,0.0004216708,0.00008872864,0.0001774303,0.0001286812,0.0001028414],"domain_scores_gemma":[0.9971035,0.001281913,0.0008207171,0.0002942788,0.0003348634,0.0001646365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001189608,0.00006662045,0.9890664,0.00001207264,0.00008591574,0.00004329775,0.00007159357,0.0008664972,0.0004845703,0.00007323981,0.0003301336,0.008780852],"study_design_scores_gemma":[0.00002474771,0.0001601757,0.9632692,0.00001818514,0.0000358527,0.0003268866,0.0002524967,0.03435979,0.0003556454,0.0008401482,0.0003456378,0.00001118275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962152,0.0001228169,0.002732189,0.0001202206,0.000009959181,0.00004050356,0.0003363292,0.00002625066,0.000396559],"genre_scores_gemma":[0.997443,0.00003039395,0.001859093,0.00003825615,0.00001410165,0.00002846097,0.0005049696,0.000004398293,0.00007730704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00254209,"threshold_uncertainty_score":0.007755935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02371565965351208,"score_gpt":0.3021961165352055,"score_spread":0.2784804568816934,"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."}}