{"id":"W4403571478","doi":"10.1101/2024.10.18.619117","title":"Packaged delivery of CRISPR-Cas9 ribonucleoproteins accelerates genome editing","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"CRISPR; Ribonucleoprotein; Genome editing; Cas9; Computational biology; Computer science; Biology; Genetics; Gene; RNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003327394,0.0007794586,0.0005161158,0.0006705371,0.0001543862,0.0006597287,0.0004084107,0.0005499604,0.02504995],"category_scores_gemma":[0.0005762697,0.0003637898,0.0005501607,0.0005343943,0.000220364,0.0004887529,0.0004478212,0.001884441,0.006926272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005607848,"about_ca_system_score_gemma":0.0003767963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006872516,"about_ca_topic_score_gemma":0.0007555194,"domain_scores_codex":[0.9996122,0.00003473012,0.00001692682,0.00010197,0.0001839425,0.00005021315],"domain_scores_gemma":[0.9997899,0.00005884538,0.00004527111,0.00003245272,0.00004487724,0.00002861404],"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":[0.0002631,0.00007631533,0.0003093844,0.0009092576,0.00007440912,0.0001779002,0.00004029774,0.004287816,0.9438726,0.003227129,0.0147627,0.03199919],"study_design_scores_gemma":[0.00005367848,0.0001549333,0.001278341,0.0000413392,0.00002725505,0.000111102,0.00001879841,0.009533182,0.9556012,0.000889103,0.03226758,0.00002359317],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3924308,0.009156793,0.4300859,0.005786308,0.005199737,0.0007008024,0.04609992,0.03624263,0.07429717],"genre_scores_gemma":[0.7903535,0.006083544,0.122844,0.0009866757,0.000278948,0.0003443037,0.01755382,0.002497405,0.05905781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02504995,"threshold_uncertainty_score":0.08380044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009419738037540516,"score_gpt":0.2425370708360154,"score_spread":0.2331173327984749,"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."}}