{"id":"W4399087850","doi":"10.1038/s41587-024-02266-4","title":"Enhancing prime editing in hematopoietic stem and progenitor cells by modulating nucleotide metabolism","year":2024,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Harvard Stem Cell Institute; Broad Institute; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; American-Italian Cancer Foundation; St. Jude Children's Research Hospital; Fred Hutchinson Cancer Research Center; Doris Duke Charitable Foundation; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Progenitor cell; Haematopoiesis; Stem cell; Nucleotide; Cell biology; Prime (order theory); Biology; Metabolism; Progenitor; Biochemistry; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001647546,0.0001823456,0.0001795372,0.0001338513,0.00003801346,0.0000344328,0.0001373346,0.0009322361,0.000003240249],"category_scores_gemma":[0.00003616026,0.0001799632,0.00004533954,0.0002000398,0.00005551889,0.000004613992,0.000152429,0.000599389,0.000003782732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000144447,"about_ca_system_score_gemma":0.00002280384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006141641,"about_ca_topic_score_gemma":0.00001662057,"domain_scores_codex":[0.9988856,0.00001821666,0.0002185471,0.0004844184,0.0000842345,0.0003089471],"domain_scores_gemma":[0.999667,0.0000158427,0.00003113431,0.0002252359,0.00001722689,0.00004351465],"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":[0.000003439513,0.000009135695,0.00005183288,0.00008334246,0.00002306949,0.00001124085,0.00004903961,0.00002119286,0.9917579,0.0003059859,0.0002820804,0.00740172],"study_design_scores_gemma":[0.0001397729,0.00003585722,0.00004664447,0.0000656275,0.0000132893,0.00004355653,0.0001288981,0.0007512096,0.9723942,0.00005133183,0.02615605,0.0001735794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9467737,0.04569368,0.00591726,0.0005629834,0.0006572453,0.0002033627,0.00001332234,0.0001277848,0.00005067506],"genre_scores_gemma":[0.9965664,0.0003232044,0.002555801,0.00005502076,0.0002874878,0.00001695068,0.00001375883,0.00003834454,0.0001430156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04979273,"threshold_uncertainty_score":0.7338688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002158548803081159,"score_gpt":0.2444653905230191,"score_spread":0.242306841719938,"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."}}