{"id":"W4387337803","doi":"10.1016/j.cjca.2023.06.329","title":"MACHINE-LEARNING FOR THE ELECTROCARDIOGRAM-BASED PREDICTION OF SHORT-TERM AND LONG-TERM MORTALITY AT THE TIME OF DISCHARGE IN A POPULATION-LEVEL COHORT OF PATIENTS WITH ACCESS TO UNIVERSAL HEALTHCARE","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Hospital Edmonton","funders":"","keywords":"Medicine; Risk stratification; Cohort; Term (time); Intensive care medicine; Acute care; Health care; Hospital discharge; Medical emergency; Emergency medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.004911683,0.0005649253,0.0009797497,0.001218983,0.0004672973,0.001227845,0.001120494,0.0009982178,0.001600359],"category_scores_gemma":[0.01634956,0.0002769917,0.0009586598,0.0007393446,0.0003343541,0.0007497729,0.0008185664,0.001798539,0.000323745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007127482,"about_ca_system_score_gemma":0.001012493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01480597,"about_ca_topic_score_gemma":0.01152078,"domain_scores_codex":[0.9987067,0.0006883653,0.00008727828,0.000265689,0.0001065318,0.0001453888],"domain_scores_gemma":[0.9934115,0.004680252,0.0006187166,0.0004683666,0.000429133,0.0003920016],"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":[0.001463199,0.0005350606,0.9513537,0.00003381245,0.0006080675,0.000191112,0.00009565848,0.02109657,0.000375912,0.0005528603,0.001461357,0.02223274],"study_design_scores_gemma":[0.0001187555,0.0004429513,0.3397956,0.00003171164,0.0001879947,0.0002688071,0.0001865237,0.6559805,0.0002585037,0.002295166,0.0003980394,0.00003549771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992128,0.0003211837,0.00566118,0.000562872,0.00004369254,0.00003456912,0.0009010308,0.00004189962,0.000305573],"genre_scores_gemma":[0.9961959,0.0001132025,0.002186077,0.00004906625,0.00004326586,0.00003084687,0.001066467,0.000006607308,0.0003085589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01480597,"threshold_uncertainty_score":0.02943957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02804672340488401,"score_gpt":0.2905445757490695,"score_spread":0.2624978523441855,"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."}}