{"id":"W1806732830","doi":"10.1186/s13059-015-0723-0","title":"Epigenome data release: a participant-centered approach to privacy protection","year":2015,"lang":"en","type":"article","venue":"Genome Biology","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; BC Cancer Agency; McGill University and Génome Québec Innovation Centre; University of British Columbia; McGill University; McGill Genome Centre","funders":"Canadian Institutes of Health Research; Deutsches Zentrum für Lungenforschung; Knut och Alice Wallenbergs Stiftelse; Interreg; European Commission; Vetenskapsrådet; Bundesministerium für Bildung und Forschung; National Institute of General Medical Sciences; European Molecular Biology Laboratory","keywords":"Epigenome; Epigenomics; ENCODE; Biology; Human genetics; DNA methylation; Computational biology; Human genome; Ambiguity; Genome; Genomics; Computer science; 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":[0.0005684294,0.0001755466,0.0001953495,0.00007344269,0.00006884139,0.00002365039,0.0005488971,0.0002056325,0.000007986822],"category_scores_gemma":[0.0003102068,0.0001644523,0.00004013759,0.0001473536,0.00005648969,0.000005270329,0.000606328,0.00008606985,0.00009083913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002800612,"about_ca_system_score_gemma":0.0001250845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006478502,"about_ca_topic_score_gemma":0.00001700565,"domain_scores_codex":[0.9983233,0.0001766612,0.0002922273,0.0007149469,0.00008998229,0.0004028838],"domain_scores_gemma":[0.9983684,0.000004965425,0.00009660903,0.001133969,0.0001179724,0.0002780786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001839942,0.000162125,0.001817857,0.00001357062,0.00006875391,8.929599e-7,0.0002459758,0.000297032,0.9907733,0.000138028,0.0002390416,0.006059405],"study_design_scores_gemma":[0.001135903,0.001347713,0.008553306,0.0000046668,0.00004532693,0.000007248745,0.0001348607,0.0005080265,0.03319817,0.0006653522,0.9538773,0.0005220685],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8983484,0.003805591,0.09416892,0.0003253883,0.0003105788,0.0007975004,0.0001459323,0.00003529169,0.00206243],"genre_scores_gemma":[0.9914675,0.0001228986,0.005290587,0.0001647824,0.0005351984,0.00009679983,0.001943947,0.00002836522,0.0003499486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9575751,"threshold_uncertainty_score":0.6706172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2313855542974254,"score_gpt":0.3367470996597274,"score_spread":0.1053615453623021,"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."}}