{"id":"W4226280654","doi":"10.1038/s41587-021-01201-1","title":"Saturation variant interpretation using CRISPR prime editing","year":2022,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":181,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; SickKids Foundation; Mount Sinai Hospital; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"CRISPR; Genome editing; Biology; Locus (genetics); Genetics; Missense mutation; Computational biology; Gene; Phenotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000138031,0.0001086365,0.00009194389,0.0001128526,0.0001518905,0.00001137618,0.0001861282,0.0004581682,0.00002712483],"category_scores_gemma":[0.0001087818,0.0001230167,0.00004873632,0.0001721287,0.00003069818,0.00000276863,0.0002437939,0.0005705688,0.000001510198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003953998,"about_ca_system_score_gemma":0.00003495592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006932121,"about_ca_topic_score_gemma":0.000006270192,"domain_scores_codex":[0.9992244,0.00003409717,0.0001422106,0.0003042321,0.0001080039,0.0001870422],"domain_scores_gemma":[0.9996111,0.000005742356,0.00006611523,0.0002621173,0.00003265307,0.00002223245],"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":[0.00003026956,0.00001734653,0.00007499652,0.000005829722,0.0000234275,0.000007057492,0.00003146494,0.002490957,0.9905221,0.00060655,0.0005417782,0.005648258],"study_design_scores_gemma":[0.0002960521,0.0002399689,0.0003103875,0.000006131774,0.00002231923,0.0002941632,0.0002421609,0.01550034,0.9275068,0.0001723235,0.05518728,0.0002220443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6890609,0.003458017,0.3028708,0.00162789,0.002140047,0.0003060316,0.00003070292,0.0001469946,0.0003586552],"genre_scores_gemma":[0.9939734,0.00002253713,0.005230528,0.0002905327,0.0002801582,0.00001626527,0.0001061685,0.00001979609,0.00006058149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3049126,"threshold_uncertainty_score":0.5016477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003830319143118978,"score_gpt":0.2836967585530153,"score_spread":0.2798664394098964,"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."}}