{"id":"W3028120919","doi":"10.1111/biom.13307","title":"A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation","year":2020,"lang":"en","type":"article","venue":"Biometrics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; HEC Montréal; Université Laval; Université du Québec à Montréal; Douglas Mental Health University Institute; McGill University; Jewish General Hospital; McGill University Health Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Compute Canada; Genome Canada","keywords":"Covariate; DNA methylation; Computer science; Inference; Bisulfite sequencing; Confounding; Computational biology; Data mining; Algorithm; Statistics; Biology; Mathematics; Artificial intelligence; Machine learning; Genetics; Gene","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":[0.0007358093,0.0001251699,0.000221814,0.0003240632,0.00003047223,0.00001616111,0.0001042505,0.0001613413,0.000001129733],"category_scores_gemma":[0.003048554,0.0001275946,0.00006638921,0.001036219,0.00001788618,0.00000437739,0.00005109155,0.00005513459,4.992104e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002929872,"about_ca_system_score_gemma":0.00009157234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005596828,"about_ca_topic_score_gemma":0.000009853846,"domain_scores_codex":[0.9988717,0.00009253372,0.0003519809,0.000314952,0.0001853846,0.0001833855],"domain_scores_gemma":[0.9992332,0.0002259547,0.000123506,0.0001313997,0.0001996968,0.00008621145],"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":[0.00008990622,0.00002747047,0.0002389575,0.0001109885,0.00003014241,4.648066e-7,0.00008720437,0.01520484,0.9672719,0.0003066141,0.000003435434,0.01662808],"study_design_scores_gemma":[0.0008392062,0.0002914804,0.0006551288,0.00001008688,0.00002912748,2.754564e-7,0.0000220529,0.309283,0.6881122,0.0004275069,0.0002028505,0.0001271272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.267013,0.0008918677,0.7316524,0.0000411049,0.00005783729,0.0002635009,0.00005720132,0.000005828859,0.00001727849],"genre_scores_gemma":[0.6723159,0.00007449981,0.3273609,0.00005315489,0.00005675817,0.0000156334,0.0001055502,0.0000159356,0.000001697527],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4053029,"threshold_uncertainty_score":0.5203156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1133910791328437,"score_gpt":0.3402896786579435,"score_spread":0.2268985995250998,"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."}}