{"id":"W4297985165","doi":"10.1016/j.xpro.2022.101734","title":"Protocol to use RNaseH1-based CRISPR to modulate locus-associated R-loops","year":2022,"lang":"en","type":"article","venue":"STAR Protocols","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"Canadian Institutes of Health Research; Ontario Ministry of Research and Innovation; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs","keywords":"Locus (genetics); Biology; Nucleic acid; CRISPR; Computational biology; Chromatin; Genetics; Chromosome conformation capture; DNA; RNA; In silico; Gene; Cell biology; Gene expression; Enhancer","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":[0.0009212453,0.001245504,0.0008507955,0.001051445,0.001130022,0.0006365069,0.001358046,0.0007792261,0.02256538],"category_scores_gemma":[0.0006860894,0.001299438,0.0007431152,0.0007130224,0.0005556647,0.0004636602,0.0008475347,0.003062317,0.01670647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005925199,"about_ca_system_score_gemma":0.001163277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007819251,"about_ca_topic_score_gemma":0.002036829,"domain_scores_codex":[0.9991946,0.0001244348,0.00009114077,0.0002044251,0.0002898501,0.00009566904],"domain_scores_gemma":[0.9994862,0.0001066416,0.00004901984,0.0001809528,0.0001015194,0.00007568888],"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":[0.0003243235,0.0002105668,0.0002009487,0.0006003483,0.00003970005,0.0003434746,0.0001323412,0.0006716544,0.9655145,0.004661703,0.0123993,0.01490103],"study_design_scores_gemma":[0.0001855354,0.0006250945,0.001518601,0.0001104286,0.0000687011,0.001085069,0.00005822852,0.00225611,0.7026542,0.002284492,0.2890418,0.0001118164],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.06116709,0.00340253,0.8286288,0.001374029,0.001294435,0.01530127,0.03388388,0.01305732,0.04189069],"genre_scores_gemma":[0.1489342,0.0067964,0.5868437,0.001588417,0.0001683471,0.03870767,0.09208439,0.002753637,0.1221232],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.02256538,"threshold_uncertainty_score":0.07548869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02317440941915121,"score_gpt":0.3608194604486877,"score_spread":0.3376450510295365,"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."}}