{"id":"W4200377454","doi":"10.1016/j.healun.2021.11.020","title":"Machine-learning–based exploration to identify remodeling patterns associated with death or heart-transplant in pediatric-dilated cardiomyopathy","year":2021,"lang":"en","type":"article","venue":"The Journal of Heart and Lung Transplantation","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cardiology; Internal medicine; Medicine; Diastole; Heart failure; Dilated cardiomyopathy; Ventricular remodeling; Ejection fraction; Systole; 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":[0.00178724,0.0005566433,0.0004082614,0.00177186,0.0002119488,0.0006418301,0.0003807665,0.0004005784,0.0009405248],"category_scores_gemma":[0.003950987,0.0001140423,0.0004640051,0.0006298771,0.0002775426,0.0003548554,0.0004517863,0.0003864062,0.0002119181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003184458,"about_ca_system_score_gemma":0.0003274557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000785081,"about_ca_topic_score_gemma":0.001264133,"domain_scores_codex":[0.9993399,0.0003117784,0.00005652907,0.0001455929,0.00007881474,0.00006724129],"domain_scores_gemma":[0.9984087,0.0008294395,0.0003756394,0.0001347106,0.0001557822,0.0000957123],"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":[0.000502353,0.0002550727,0.8886843,0.00008491148,0.0002260446,0.0002287212,0.0002432988,0.01334803,0.00565193,0.0003790634,0.0005996004,0.08979652],"study_design_scores_gemma":[0.00004802733,0.0006173137,0.6735234,0.00005085863,0.0001019199,0.0008973359,0.0004173569,0.3159732,0.004410087,0.002710838,0.001218478,0.00003116204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747488,0.0003545581,0.02362909,0.0001786968,0.00001071007,0.00004903214,0.000481665,0.000147398,0.0004000591],"genre_scores_gemma":[0.9888656,0.00005262845,0.01039948,0.00002451479,0.00001234745,0.00003466513,0.000470872,0.000008977515,0.0001308591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00178724,"threshold_uncertainty_score":0.009451985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02392875681161178,"score_gpt":0.2820916446584108,"score_spread":0.258162887846799,"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."}}