{"id":"W4399285409","doi":"10.7554/elife.91288.3","title":"Near-perfect precise on-target editing of human hematopoietic stem and progenitor cells","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"Fonds de Recherche du Québec - Santé; Terry Fox Research Institute; Cancer Research Society","keywords":"Genome editing; Progenitor cell; Stem cell; Biology; Haematopoiesis; Computational biology; CRISPR; Cord blood; Primary cell; Genetics; Cell; Gene","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":[0.0005250594,0.0003269715,0.0003221692,0.0001677943,0.0001720778,0.0006307434,0.0003532943,0.0003253359,0.001872452],"category_scores_gemma":[0.0004000581,0.0001522406,0.0002038897,0.0001193673,0.0002624239,0.0001888009,0.0003629492,0.0006732316,0.0006547584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002550869,"about_ca_system_score_gemma":0.0003154938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005106447,"about_ca_topic_score_gemma":0.001083441,"domain_scores_codex":[0.9996418,0.00007296312,0.00002738054,0.00008531067,0.0001228912,0.00004968896],"domain_scores_gemma":[0.9998156,0.00004719903,0.00003575776,0.00004650017,0.00002626293,0.00002866995],"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":[0.00004236303,0.00001450699,0.0001334633,0.00004015628,0.00000623692,0.00004734608,0.00002468687,0.0003395838,0.992419,0.0005003135,0.0001765685,0.00625586],"study_design_scores_gemma":[0.000004383847,0.0000549261,0.0004450739,0.00000508899,0.000007445635,0.0001481487,0.00001117614,0.0007931615,0.9930887,0.0001615839,0.005276208,0.000004163452],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7251036,0.001830345,0.2567683,0.0003422839,0.0001580312,0.0002723375,0.001596945,0.001407147,0.01252099],"genre_scores_gemma":[0.9088024,0.001381465,0.07790463,0.0001651343,0.00002130171,0.0000933103,0.001696549,0.0003092516,0.009625834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001872452,"threshold_uncertainty_score":0.006263971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007287696831792061,"score_gpt":0.2850515279794004,"score_spread":0.2777638311476083,"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."}}