{"id":"W4412796434","doi":"10.1038/s41467-025-62218-7","title":"Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"GDF15 and Related Biomarkers","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; McMaster University; Population Health Research Institute","funders":"Daiichi Sankyo Europe; MicroPort; Mach-Gaensslen Foundation of Canada; Biosense Webster; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Foundation for Cardiovascular Research; Schweizerische Herzstiftung; Universität Basel; AstraZeneca; Pfizer; Boston Scientific Corporation; National Science Foundation","keywords":"Medicine; Biomarker; Atrial fibrillation; Internal medicine; Natriuretic peptide; Heart failure; Myocardial infarction; GDF15; Cardiology; Troponin; Stroke (engine); Brain natriuretic peptide; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001228799,0.00009562555,0.0001583352,0.0001676923,0.0001631169,0.00001123337,0.00009733226,0.0004524333,0.000001617958],"category_scores_gemma":[0.0003112684,0.00006296622,0.00005408706,0.0003656859,0.0001130548,0.00005200355,0.00006393378,0.0003797715,4.770383e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000521852,"about_ca_system_score_gemma":0.00005033654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001218581,"about_ca_topic_score_gemma":0.00004285479,"domain_scores_codex":[0.9993649,0.00008578427,0.0002126362,0.0001792678,0.0000549089,0.0001024753],"domain_scores_gemma":[0.9989577,0.0002852486,0.00008782512,0.000468155,0.0001645141,0.00003656677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004324446,0.0001960266,0.9319953,0.00004175802,0.0004805629,1.611467e-7,0.0002740186,0.000007445428,0.007209691,0.0008237083,0.0004088424,0.054238],"study_design_scores_gemma":[0.004964819,0.0002550288,0.9836864,0.00009630983,0.0001285445,4.462012e-7,0.00003499802,0.002405114,0.0001909927,0.0002329255,0.007935895,0.00006848203],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924302,0.003379182,0.0003997821,0.001419397,0.0001615808,0.001431038,0.0000587778,0.00005410371,0.0006660055],"genre_scores_gemma":[0.9954386,0.001281398,0.002505989,0.00007940661,0.00002470543,0.00001798143,0.0005957989,0.000006306406,0.00004983539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05416951,"threshold_uncertainty_score":0.348958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297817943637944,"score_gpt":0.2823971910624788,"score_spread":0.2694190116260993,"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."}}