{"id":"W4406404907","doi":"10.1038/s41467-025-56054-y","title":"Causality-driven candidate identification for reliable DNA methylation biomarker discovery","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; H. Lundbeck A/S; Servier; National Natural Science Foundation of China; Eisai; Genentech; IXICO; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Canadian Institutes of Health Research; Natural Science Foundation of Shanghai; F. Hoffmann-La Roche; University of Southern California; Shanghai Municipal Education Commission; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association","keywords":"Biomarker discovery; Computational biology; DNA methylation; Identification (biology); Biomarker; Causality (physics); Biology; Genetics; Computer science; Bioinformatics; Gene; Proteomics; Gene expression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072189,0.000896118,0.001372581,0.002237259,0.0006221006,0.001366359,0.001838077,0.001275979,0.002664989],"category_scores_gemma":[0.01882584,0.0005508242,0.001156612,0.001546466,0.001372941,0.001924178,0.002911687,0.001843709,0.0005378605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009473134,"about_ca_system_score_gemma":0.003434846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00163564,"about_ca_topic_score_gemma":0.002286723,"domain_scores_codex":[0.998268,0.0007640905,0.0001130596,0.0003797864,0.000352159,0.0001229354],"domain_scores_gemma":[0.9924321,0.005153958,0.0006960508,0.0007071674,0.0007620426,0.0002487224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009399963,0.000345189,0.02517556,0.001161697,0.000527236,0.0007393245,0.0003542303,0.3824399,0.03089585,0.1617039,0.007738733,0.3879784],"study_design_scores_gemma":[0.00005222051,0.00006590113,0.001117689,0.00004524686,0.0000752037,0.0001053941,0.00002503196,0.8904324,0.007347092,0.097794,0.002910194,0.00002961476],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01607763,0.0006180719,0.9809569,0.0007148993,0.00004536795,0.00007050898,0.0003124284,0.0005156209,0.0006884823],"genre_scores_gemma":[0.5956049,0.00107035,0.3974611,0.0008906683,0.0002231369,0.0003901777,0.001451084,0.00019788,0.002710662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0072189,"threshold_uncertainty_score":0.03817761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02126582704715797,"score_gpt":0.3466346511359822,"score_spread":0.3253688240888242,"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."}}