{"id":"W4210830730","doi":"10.1093/eurheartj/ehab849.044","title":"Clustering analysis based on automated electrocardiographic measurements to identify prognostically distinct phenotypes in patients hospitalized for heart failure: a retrospective cohort study","year":2022,"lang":"en","type":"article","venue":"European Heart Journal","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Calgary","funders":"","keywords":"Medicine; Cohort; Internal medicine; Cardiology; QRS complex; Heart failure; Retrospective cohort study; Proportional hazards model; Electrocardiography; Left ventricular hypertrophy; Heart disease; Cohort study; Blood pressure","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":[0.001416521,0.0004063699,0.0005844755,0.001812273,0.0006889973,0.0008258991,0.000647339,0.0005611398,0.0008858416],"category_scores_gemma":[0.003644923,0.0004144759,0.0009065813,0.001553834,0.0003406154,0.0005818961,0.0007322619,0.0005264332,0.0002215061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005090206,"about_ca_system_score_gemma":0.0005344636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005707425,"about_ca_topic_score_gemma":0.005409783,"domain_scores_codex":[0.9986666,0.0003283895,0.0001861908,0.0004645978,0.0002045733,0.0001496031],"domain_scores_gemma":[0.9973008,0.0004035879,0.001172974,0.0004393495,0.0004047453,0.0002786974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001390843,0.00003511974,0.998584,0.00001110887,0.00009438582,0.00007733903,0.0001193094,0.00004619918,0.0001376366,0.00001423274,0.0000883858,0.0006532985],"study_design_scores_gemma":[0.00001712276,0.0001532119,0.9981324,0.0000100144,0.00006680405,0.0003581391,0.0003886208,0.0006773406,0.00005424826,0.00003517212,0.00009540498,0.00001152988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993379,0.0001058922,0.0001863397,0.00001371859,0.000004539806,0.00002794626,0.0002334103,0.000002774995,0.00008752872],"genre_scores_gemma":[0.999274,0.0000515661,0.0002142474,0.00001181051,0.000006059269,0.0000253976,0.0003788333,0.000002269181,0.00003583026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005707425,"threshold_uncertainty_score":0.01134837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02244174449304731,"score_gpt":0.3137643118007488,"score_spread":0.2913225673077015,"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."}}