{"id":"W4214840711","doi":"10.1089/crispr.2021.0109","title":"Increasing the Targeting Scope of CRISPR Base Editing System Beyond NGG","year":2022,"lang":"en","type":"review","venue":"The CRISPR Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"CRISPR; Genome editing; Cas9; Scope (computer science); Computational biology; Biology; Point mutation; DNA; Workflow; Computer science; Base pair; Genetics; Mutation; Gene; Programming language; Database","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":[0.0004493287,0.0005342545,0.0007929833,0.001665542,0.0001585842,0.0007409373,0.0005474798,0.0007105471,0.002166278],"category_scores_gemma":[0.0004242442,0.0002315449,0.0004915749,0.0009855833,0.0003102527,0.0008766468,0.0004326674,0.001227526,0.001274411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000379895,"about_ca_system_score_gemma":0.0006719422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005329217,"about_ca_topic_score_gemma":0.0007260806,"domain_scores_codex":[0.999733,0.00003826063,0.00002671384,0.00005376777,0.0001226273,0.00002560967],"domain_scores_gemma":[0.9997972,0.0001012821,0.00003497576,0.00001005895,0.00003826651,0.00001831327],"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":[0.00007403572,0.00005616089,0.0002656976,0.01463078,0.00009900179,0.000396684,0.0000633794,0.0006183183,0.04122728,0.007405762,0.01215685,0.9230061],"study_design_scores_gemma":[0.00001784848,0.0001467455,0.0006882096,0.0009970549,0.000127932,0.002641357,0.00002920711,0.0003511905,0.01952639,0.001856727,0.9735844,0.00003278902],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001412786,0.9869972,0.004271782,0.0004341412,0.0002396372,0.000023054,0.00006089859,0.00009562291,0.006464782],"genre_scores_gemma":[0.009608147,0.9816245,0.004775463,0.0004969151,0.0001612901,0.00002707958,0.000139518,0.00001900412,0.003148046],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002166278,"threshold_uncertainty_score":0.007246912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02184174884512836,"score_gpt":0.3347463353584101,"score_spread":0.3129045865132817,"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."}}