{"id":"W3128912337","doi":"10.1111/febs.15750","title":"Clinical advances in targeting epigenetics for cancer therapy","year":2021,"lang":"en","type":"review","venue":"FEBS Journal","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Ontario Institute for Cancer Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Epigenetics; Cancer therapy; Epigenetic therapy; Cancer; Medicine; Computational biology; Biology; Bioinformatics; DNA methylation; Internal medicine; Genetics","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":[0.0007152731,0.0002200175,0.0007100573,0.00005957097,0.00008004807,0.00005287836,0.0002363182,0.0003603878,0.00006495765],"category_scores_gemma":[0.0003115181,0.0001720521,0.0006028643,0.00009664067,0.00003735345,0.000004934773,0.00004913264,0.0004075572,0.00000217402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003020426,"about_ca_system_score_gemma":0.0006243028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.536529e-7,"about_ca_topic_score_gemma":0.00001132748,"domain_scores_codex":[0.9982289,0.0002712021,0.0008375011,0.0003032055,0.0001139025,0.0002452674],"domain_scores_gemma":[0.9990748,0.00004515804,0.0004855532,0.0001634233,0.000136861,0.00009418044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009613103,0.00003638616,0.0000892738,0.0002976251,0.0000574449,0.000004000832,0.000003059484,0.00000397615,0.00002761695,0.000005882992,0.005090429,0.9943747],"study_design_scores_gemma":[0.000365559,0.0001295534,0.000003398305,0.001823109,0.00003348252,0.00002680431,0.00000909852,0.00000172583,0.0002366013,0.00002263973,0.9971395,0.0002085589],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005598837,0.9971676,0.0009206044,0.00004016792,0.00135263,0.000339096,0.00003209947,0.000002742458,0.00008899712],"genre_scores_gemma":[0.000005616936,0.9936016,0.00220692,0.0001264051,0.003311885,0.00008950669,0.0001777216,0.00004014391,0.0004402079],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9941661,"threshold_uncertainty_score":0.7016081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0727116662767061,"score_gpt":0.4457635415172905,"score_spread":0.3730518752405844,"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."}}