{"id":"W2145082576","doi":"10.1186/1745-6215-14-123","title":"Methods of creatine kinase-MB analysis to predict mortality in patients with myocardial infarction treated with reperfusion therapy","year":2013,"lang":"en","type":"article","venue":"Trials","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alexion Pharmaceuticals","keywords":"Medicine; Myocardial infarction; Internal medicine; Cardiology; Hazard ratio; Creatine kinase; Percutaneous coronary intervention; Conventional PCI; Heart failure; Proportional hazards model; Infarction; Stroke (engine); Confidence interval","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":[0.0297405,0.001468369,0.001579796,0.003848179,0.0002458169,0.001628155,0.001133226,0.0006730523,0.001447403],"category_scores_gemma":[0.07093048,0.0004717357,0.001598889,0.001974565,0.0005732753,0.0007102682,0.001436294,0.001290965,0.0004131387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007246566,"about_ca_system_score_gemma":0.00164961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001040039,"about_ca_topic_score_gemma":0.00132642,"domain_scores_codex":[0.9734077,0.01941625,0.001376131,0.001612107,0.003940438,0.0002472963],"domain_scores_gemma":[0.9505735,0.03121276,0.009782183,0.00315148,0.004733193,0.0005468925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006167668,0.0006968913,0.7752119,0.0007324605,0.005069396,0.0001291535,0.0003936334,0.01182372,0.0020496,0.00247851,0.003757918,0.191489],"study_design_scores_gemma":[0.001560079,0.004297276,0.7280484,0.0004734062,0.00189535,0.001140881,0.0003380074,0.2414342,0.004026321,0.008404937,0.00812089,0.0002601169],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4967904,0.01434605,0.4676804,0.001892922,0.0005775402,0.003175085,0.003888694,0.001245936,0.01040306],"genre_scores_gemma":[0.9018728,0.00182497,0.09038724,0.0003479943,0.0002544658,0.002507398,0.00155055,0.0001136989,0.00114091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0297405,"threshold_uncertainty_score":0.1572847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07905415261826075,"score_gpt":0.4182845157950457,"score_spread":0.3392303631767849,"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."}}