{"id":"W4285045763","doi":"10.1016/j.ymthe.2022.07.010","title":"A precise and efficient adenine base editor","year":2022,"lang":"en","type":"article","venue":"Molecular Therapy","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"National Institutes of Health","keywords":"Bystander effect; Genome editing; Computational biology; Mutation; Gene; Biology; Genetics; Genome","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001087216,0.0001078129,0.00007685318,0.00003316457,0.00009018131,0.0000132805,0.0001115932,0.00003301004,0.00007801171],"category_scores_gemma":[0.00001030652,0.0001113202,0.00005266324,0.0000670773,0.00002194935,4.854399e-7,0.0001231115,0.00007625615,0.000002639902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007698044,"about_ca_system_score_gemma":0.0000187507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003912383,"about_ca_topic_score_gemma":4.174803e-7,"domain_scores_codex":[0.9993174,0.00004164049,0.00008900675,0.000252828,0.000140634,0.0001584781],"domain_scores_gemma":[0.9996505,0.000003940236,0.00001989152,0.000245442,0.00001728468,0.00006295243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007107574,0.00005319629,0.00006354066,0.000003254211,0.00002699221,0.00001175024,0.00005881362,0.008715105,0.9845362,0.00001368878,0.002177938,0.004268404],"study_design_scores_gemma":[0.001014047,0.0004469702,0.0003297747,0.000002091348,0.000006842951,0.00003895911,0.00005861924,0.001323502,0.7142528,0.00001408616,0.2823008,0.0002115237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776759,0.00808628,0.01314681,0.0001763937,0.0005549165,0.00018204,0.00001910505,0.00001645611,0.0001420761],"genre_scores_gemma":[0.998183,0.0001499259,0.0005758962,0.000285273,0.0004133034,0.00008159935,0.00004939717,0.00002709745,0.0002345752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2801228,"threshold_uncertainty_score":0.4539506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004072216163870348,"score_gpt":0.2546094067775029,"score_spread":0.2505371906136326,"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."}}