{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00102085,0.0004527867,0.0005698747,0.0002664283,0.000308832,0.0008268495,0.0007274488,0.0005085151,0.002933414],"category_scores_gemma":[0.0006176414,0.0003344278,0.000326135,0.0002537574,0.0003463829,0.0002229197,0.0008097999,0.000913916,0.002084767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002234991,"about_ca_system_score_gemma":0.00035172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003442009,"about_ca_topic_score_gemma":0.0007860415,"domain_scores_codex":[0.9988752,0.0002540615,0.00009436212,0.0003046628,0.0003702168,0.0001015389],"domain_scores_gemma":[0.9995291,0.0001197222,0.0000728928,0.0001624611,0.00005760123,0.00005825899],"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":[0.00008085497,0.00003698105,0.0001971825,0.00004754406,0.00001249388,0.0001158486,0.00005542081,0.0002283382,0.9898391,0.0009755487,0.0005423606,0.007868432],"study_design_scores_gemma":[0.00001840633,0.0001403496,0.0004379122,0.000007657804,0.0000173485,0.0006062428,0.00001364005,0.002200425,0.9782744,0.000168617,0.01810353,0.00001141136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2943532,0.001732194,0.6880459,0.0003837851,0.0003109532,0.001379512,0.001156337,0.002624287,0.01001386],"genre_scores_gemma":[0.7190632,0.001263884,0.2612728,0.0002237299,0.00006261475,0.001085278,0.001942641,0.0006201174,0.01446585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002933414,"threshold_uncertainty_score":0.009813249,"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."}}