{"id":"W4410611372","doi":"10.1371/journal.pgen.1011667","title":"Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing","year":2025,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute of General Medical Sciences; National Cancer Institute; National Institute of Mental Health; Hevolution Foundation; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research; Canada Research Chairs; Pew Charitable Trusts; National Institutes of Health; National Science Foundation; Kinship Foundation; Burroughs Wellcome Fund; Agence Nationale de la Recherche","keywords":"Biology; DNA methylation; Throughput; Computational biology; DNA sequencing; DNA; Genetics; Methylation; Gene; Gene expression; Computer science","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":[0.0003164345,0.0001897554,0.0001900609,0.00009294365,0.0002555777,0.00004143151,0.0001556375,0.0002142115,0.000007454904],"category_scores_gemma":[0.0003160051,0.0002031554,0.0000996268,0.0001801835,0.00006252098,0.000004476698,0.0001173462,0.00007829865,0.000007130802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009249502,"about_ca_system_score_gemma":0.0001604912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005540065,"about_ca_topic_score_gemma":0.00004469821,"domain_scores_codex":[0.9986866,0.000105169,0.0003130221,0.0004011941,0.0001322843,0.000361761],"domain_scores_gemma":[0.9990354,0.0001105111,0.000114872,0.0004028266,0.0002757383,0.00006063642],"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":[0.00002766388,0.00005883007,0.0002284251,0.00007632582,0.0001352702,2.187693e-7,0.0000764566,0.003411007,0.9833599,0.001505019,0.000275879,0.010845],"study_design_scores_gemma":[0.0006161119,0.0002345652,0.0005570601,0.00003182499,0.0001425001,3.402715e-7,0.00006271473,0.008336185,0.9740618,0.007378653,0.008367022,0.0002111903],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6655831,0.004449349,0.3257743,0.0002401987,0.0004062188,0.002509701,0.000071722,0.0000338696,0.0009315257],"genre_scores_gemma":[0.9880227,0.0003504366,0.009663064,0.0001827554,0.0002473257,0.0007842097,0.0003290625,0.00003188739,0.0003885054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3224396,"threshold_uncertainty_score":0.8284437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04808362014828348,"score_gpt":0.3123663205342957,"score_spread":0.2642827003860122,"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."}}