{"id":"W4366829167","doi":"10.3390/biomedicines11051238","title":"Increasing Specificity of Targeted DNA Methylation Editing by Non-Enzymatic CRISPR/dCas9-Based Steric Hindrance","year":2023,"lang":"en","type":"review","venue":"Biomedicines","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Faculty of Medicine and Health, University of Sydney; McGill University","keywords":"Epigenetics; Epigenome; CRISPR; Genome editing; DNA methylation; Computational biology; Biology; DNA; Genetics; Bioinformatics; Gene; Gene expression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005026133,0.0006290142,0.0007311482,0.001157532,0.0001747483,0.0006236426,0.0006799965,0.0007300635,0.002516245],"category_scores_gemma":[0.0004089918,0.000241022,0.0003704805,0.0008319708,0.0004109968,0.0008375926,0.0005001935,0.001357493,0.001447101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005404804,"about_ca_system_score_gemma":0.0005525523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004650317,"about_ca_topic_score_gemma":0.0007937517,"domain_scores_codex":[0.9997913,0.0000356443,0.00002119886,0.00004592458,0.00008282088,0.00002305134],"domain_scores_gemma":[0.9998078,0.000107408,0.00002960097,0.0000096854,0.00003381214,0.00001170222],"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":[0.00006514337,0.00006104405,0.0001589823,0.01983064,0.0001011695,0.000500623,0.00007924739,0.0008524923,0.06328593,0.0189254,0.01689185,0.8792474],"study_design_scores_gemma":[0.00001118458,0.0000971136,0.0003599121,0.0007435283,0.00006894606,0.002034527,0.00002369176,0.000190037,0.02248512,0.001964104,0.9719989,0.00002308034],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001234438,0.9846891,0.004654199,0.0004976547,0.0004127226,0.00002008301,0.00005147323,0.00007137054,0.008368934],"genre_scores_gemma":[0.008164943,0.9837943,0.002776651,0.0004239364,0.0001613218,0.00002684628,0.0001056269,0.0000141118,0.004532316],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002516245,"threshold_uncertainty_score":0.008417666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02655895106238309,"score_gpt":0.3539314303216908,"score_spread":0.3273724792593077,"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."}}