{"id":"W4303199315","doi":"10.1038/s41467-022-33669-z","title":"Marker-free co-selection for successive rounds of prime editing in human cells","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Selection (genetic algorithm); Prime (order theory); Computer science; Computational biology; Genome editing; Biology; Genetics; Artificial intelligence; CRISPR; Gene; Combinatorics; Mathematics","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":[0.0002035382,0.00006037689,0.00007489604,0.00005955519,0.0001906954,0.000006312498,0.0005961648,0.00009242375,0.000009790858],"category_scores_gemma":[0.00007874762,0.00007346672,0.00004833865,0.0001269215,0.00002888757,0.000002179588,0.0003074915,0.0002897095,9.476382e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000267702,"about_ca_system_score_gemma":0.00003048192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002300963,"about_ca_topic_score_gemma":0.0003713338,"domain_scores_codex":[0.9995125,0.00005427582,0.0001507708,0.0001148926,0.00006818124,0.00009939416],"domain_scores_gemma":[0.9991499,0.00004610598,0.00007116429,0.0006548295,0.00006190009,0.00001614877],"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":[0.00001471617,0.00008327325,0.00320864,0.00001324013,0.00001986979,5.383476e-8,0.00007010133,0.001145835,0.990268,0.0008139513,0.003857529,0.0005047949],"study_design_scores_gemma":[0.0009517132,0.0002451207,0.005210342,0.00001285725,0.00002346711,0.000004494043,0.000433804,0.004086618,0.846029,0.0002023236,0.1425931,0.0002071399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9391283,0.01513645,0.03340293,0.001607373,0.0006963241,0.001501078,0.0005362674,0.00005569764,0.007935565],"genre_scores_gemma":[0.994548,0.00004933984,0.004574026,0.00004426872,0.00006584301,0.0001281585,0.0004133967,0.00001252829,0.0001644395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.144239,"threshold_uncertainty_score":0.2995886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009122689201274632,"score_gpt":0.3412505014385889,"score_spread":0.3321278122373143,"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."}}