{"id":"W4283070781","doi":"10.1038/s41467-022-31270-y","title":"Peptide fusion improves prime editing efficiency","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec","funders":"Qatar Biomedical Research Institute, Hamad Bin Khalifa University; National Human Genome Research Institute; Fundação de Amparo à Pesquisa do Estado de São Paulo; American Heart Association; U.S. Department of Health and Human Services","keywords":"Prime (order theory); Computer science; Genome editing; Translation (biology); Computational biology; Peptide; Function (biology); Biology; Genome; Biochemistry; Cell biology; Gene; Mathematics","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":[0.0001610237,0.00007158033,0.00005326905,0.00003467243,0.000431801,0.00001164585,0.0006608417,0.00007641326,0.00001847533],"category_scores_gemma":[0.00009040301,0.00007830764,0.00005091799,0.0001253301,0.0000333282,0.000001458056,0.0009523732,0.000442251,0.000002667745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001627052,"about_ca_system_score_gemma":0.00003328032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005968125,"about_ca_topic_score_gemma":0.00002878349,"domain_scores_codex":[0.9994684,0.00004913882,0.0001077084,0.0001463171,0.0001025666,0.0001258466],"domain_scores_gemma":[0.9989006,0.00001895955,0.00003960123,0.0009673611,0.00004127675,0.00003219101],"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":[0.000004472067,0.0000684668,0.0004502163,0.000003196277,0.00001145644,2.695579e-7,0.00009402761,0.00033123,0.9911556,0.0004463886,0.004676335,0.002758399],"study_design_scores_gemma":[0.0002610889,0.0001362338,0.004697694,0.000004756614,0.00001658118,0.00002374405,0.0004783658,0.003039208,0.07213908,0.00003520629,0.9189577,0.0002103774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8917235,0.05915281,0.01033991,0.005568732,0.00157781,0.0007778013,0.0001193731,0.0001752936,0.03056475],"genre_scores_gemma":[0.9944765,0.0001875629,0.004109379,0.0002368969,0.0001294257,0.00005283426,0.0002590064,0.00001379606,0.0005346124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9190165,"threshold_uncertainty_score":0.3321108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006614344046970064,"score_gpt":0.3022269127878583,"score_spread":0.2956125687408882,"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."}}