{"id":"W2129915465","doi":"10.1186/s13059-014-0503-2","title":"Functional normalization of 450k methylation array data improves replication in large cancer studies","year":2014,"lang":"en","type":"article","venue":"Genome biology","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1009,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital; University of Toronto; Ontario Institute for Cancer Research; Ottawa Hospital; McGill University; Douglas Mental Health University Institute","funders":"National Institute of Dental and Craniofacial Research; National Institute of General Medical Sciences; National Cancer Institute","keywords":"Biology; Human genetics; Methylation; Computational biology; Normalization (sociology); Replication (statistics); DNA methylation; Genetics; Cancer; Epigenetics; Bioinformatics; Evolutionary biology; Gene; Gene expression","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":[0.0006203512,0.00009390758,0.0001516143,0.00007537071,0.00004045765,0.000003706404,0.0001583763,0.0001381489,0.0000134427],"category_scores_gemma":[0.0003329236,0.00008775579,0.00002452867,0.0001142949,0.00005288624,0.000007074492,0.0001167019,0.00004213786,0.000001850929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001742941,"about_ca_system_score_gemma":0.00003885645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004082853,"about_ca_topic_score_gemma":0.0002401134,"domain_scores_codex":[0.9989484,0.0001292817,0.0002957241,0.0004237466,0.00005505107,0.0001478281],"domain_scores_gemma":[0.9989948,0.00002677887,0.0001867622,0.0006229334,0.0001465649,0.00002210756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003136972,0.0000280143,0.02333702,0.00001860622,0.00003468178,1.530223e-8,0.00005834522,0.0003158309,0.9713203,0.0005423431,0.0000251739,0.004288304],"study_design_scores_gemma":[0.0009600652,0.0003772965,0.2295415,0.00001132917,0.00003788307,5.913712e-7,0.0001204848,0.001372733,0.705328,0.003155758,0.05881368,0.0002806829],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8931601,0.01289354,0.09299666,0.0001795139,0.0002765068,0.000195811,0.0001042367,0.000007782236,0.0001858295],"genre_scores_gemma":[0.9935068,0.002224205,0.0008446136,0.00006993875,0.000275982,0.00003099493,0.002949828,0.00001021436,0.00008744943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2659923,"threshold_uncertainty_score":0.3578577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05226886351996257,"score_gpt":0.3455371985945553,"score_spread":0.2932683350745928,"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."}}