{"id":"W4400578756","doi":"10.1093/ehjdh/ztae051","title":"Machine learning-based prediction of 1-year all-cause mortality in patients undergoing CRT implantation: validation of the SEMMELWEIS-CRT score in the European CRT Survey I dataset","year":2024,"lang":"en","type":"article","venue":"European Heart Journal - Digital Health","topic":"Cardiac pacing and defibrillation studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nemzeti Kutatási Fejlesztési és Innovációs Hivatal; Nemzeti Kutatási, Fejlesztési és Innovaciós Alap; Ministry of Advanced Education; Magyar Tudományos Akadémia; European Commission","keywords":"Medicine; Cardiac resynchronization therapy; Receiver operating characteristic; Internal medicine; Cohort; Heart failure; Odds ratio; Area under the curve; Ejection fraction; Cardiology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004232053,0.000145537,0.0003281841,0.0001991096,0.0001304848,0.0001090378,0.00006105667,0.00001890437,0.00000385636],"category_scores_gemma":[0.000565331,0.00009452552,0.000122047,0.0005001663,0.00006724272,0.0002508073,0.00006036807,0.000470605,0.00001768668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001108791,"about_ca_system_score_gemma":0.0002113537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001598938,"about_ca_topic_score_gemma":0.00008126781,"domain_scores_codex":[0.9960084,0.002128733,0.0008477739,0.0002104804,0.000591767,0.0002128529],"domain_scores_gemma":[0.9988236,0.0004291006,0.0002739422,0.0002626952,0.0001234254,0.00008718859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001129658,0.000105942,0.9920902,0.0001883172,0.00007726636,0.00001980487,0.0006881719,0.00126919,0.000005644641,0.00000574385,0.004901452,0.0005352724],"study_design_scores_gemma":[0.001056628,0.0004488826,0.9946508,0.0007972841,0.00003841675,0.0001593055,0.0001711033,0.0001261534,0.00001263062,0.000007859381,0.002466866,0.00006409529],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918062,0.0003342251,0.00005993806,0.0003826351,0.0003013849,0.0003270631,0.001921111,0.00002567807,0.004841777],"genre_scores_gemma":[0.997622,0.0001345198,0.00001001479,0.0002339344,0.0001317839,5.828717e-7,0.001814086,0.00002990533,0.00002320194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005815783,"threshold_uncertainty_score":0.3854639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1207262393877813,"score_gpt":0.3622328724889506,"score_spread":0.2415066331011693,"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."}}