{"id":"W4382198867","doi":"10.1093/bib/bbad241","title":"<i>E</i> -value: a superior alternative to <i>P</i> -value and its adjustments in DNA methylation studies","year":2023,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; Zhejiang University; National Natural Science Foundation of China; Natural Science Foundation of Shanghai; University of Waterloo; Shanghai Normal University; American Heart Association","keywords":"Benchmarking; DNA methylation; Statistical power; Decitabine; Statistics; Methylation; Value (mathematics); Computational biology; Computer science; Biology; Data mining; Mathematics; Genetics; Gene; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005637108,0.0001724326,0.000211767,0.0002220503,0.00005423055,0.0000326308,0.0001168393,0.0001129236,0.000001098947],"category_scores_gemma":[0.0004792972,0.0001734783,0.00003301344,0.0004533205,0.00003412315,0.0000216457,0.0002289937,0.00008435324,0.00002106095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004137282,"about_ca_system_score_gemma":0.00003733191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004683833,"about_ca_topic_score_gemma":0.00006304641,"domain_scores_codex":[0.9987811,0.00004967737,0.0004621934,0.0002249731,0.0001924432,0.0002896008],"domain_scores_gemma":[0.9995479,0.00004771961,0.00009790057,0.0001605841,0.00007506365,0.00007083292],"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":[0.0003815436,0.0002485924,0.02054354,0.001013474,0.0003064205,0.0000396595,0.03419574,0.03827844,0.8111489,0.005065392,0.003057453,0.08572089],"study_design_scores_gemma":[0.003526531,0.0007889061,0.05062431,0.0004074681,0.0000408366,0.000008497867,0.002652916,0.05786929,0.8548229,0.003254531,0.02494508,0.001058736],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962704,0.001807153,0.000363145,0.0005591348,0.000131799,0.0004306715,0.00002234451,0.00001843244,0.0003969852],"genre_scores_gemma":[0.9877465,0.005463194,0.004793462,0.001544216,0.00007193316,0.00008099074,0.0001075974,0.00002782625,0.0001642839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08466215,"threshold_uncertainty_score":0.7074238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02855293164964317,"score_gpt":0.3179497079419852,"score_spread":0.2893967762923421,"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."}}