{"id":"W2046497507","doi":"10.1016/j.ahj.2005.04.009","title":"Predicting early mortality after implantable defibrillator implantation: A clinical risk score for optimal patient selection","year":2006,"lang":"en","type":"article","venue":"American Heart Journal","topic":"Cardiac pacing and defibrillation studies","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen Elizabeth II Health Sciences Centre","funders":"","keywords":"Medicine; Framingham Risk Score; Internal medicine; Implantable cardioverter-defibrillator; Logistic regression; Cohort; Retrospective cohort study; Mortality rate; Risk assessment; Atrial fibrillation; Cohort study; Odds ratio; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005052336,0.0001681133,0.0006845873,0.0001087298,0.0003942312,0.00007574377,0.00001137528,0.00005515006,0.000007276666],"category_scores_gemma":[0.000157329,0.0001432151,0.0004468686,0.0002372058,0.0001348649,0.0001246911,0.00002113804,0.0002879231,0.00001372385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008727668,"about_ca_system_score_gemma":0.0001507152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009826903,"about_ca_topic_score_gemma":0.0000449238,"domain_scores_codex":[0.9981504,0.0001331536,0.0007172119,0.0002731416,0.0003500918,0.0003759697],"domain_scores_gemma":[0.9986568,0.0003029183,0.0003944086,0.0001293651,0.0003190591,0.0001974309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006900433,0.00003396863,0.9888291,0.00001161061,0.0002090154,0.000005013901,0.0001259058,0.0002606638,0.0001039947,0.000003229465,0.007538882,0.002188565],"study_design_scores_gemma":[0.0007865957,0.001327951,0.9774543,0.00005562128,0.0003314443,0.006707936,0.0002534972,0.0001505205,0.0001684348,0.00002484136,0.01258895,0.0001498951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954759,0.0003038429,0.001568092,0.00005348555,0.0004158653,0.0003140216,0.00009898269,0.00007639179,0.001693347],"genre_scores_gemma":[0.9923022,0.00009706272,0.005231638,0.0001935054,0.002072978,0.00002286257,0.0000114028,0.00002594173,0.00004235707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01137479,"threshold_uncertainty_score":0.5840142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03150192554224278,"score_gpt":0.3507393513969209,"score_spread":0.3192374258546781,"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."}}