{"id":"W4387341290","doi":"10.1038/s41467-023-41829-y","title":"PAM-flexible genome editing with an engineered chimeric Cas9","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Vallee Foundation; CHDI Foundation; Howard Hughes Medical Institute; National Heart, Lung, and Blood Institute; Krembil Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Cancer Institute; National Institutes of Health; National Science Foundation","keywords":"Cas9; Genome editing; CRISPR; Computational biology; Genome engineering; Genome; Limiting; Protein engineering; Biology; Translation (biology); Computer science; Genetics; Enzyme; Messenger RNA; Gene; Biochemistry","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":[0.0001075917,0.0001073144,0.00007962409,0.00007454916,0.0001472971,0.00002145841,0.0005203108,0.0001573185,0.000006336368],"category_scores_gemma":[0.00004517661,0.000101811,0.00003284281,0.00037255,0.00004155857,0.000004147133,0.0001827575,0.0002977301,0.00001556915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007761161,"about_ca_system_score_gemma":0.00002997376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008489193,"about_ca_topic_score_gemma":0.0001274345,"domain_scores_codex":[0.9994306,0.00002621807,0.0001011936,0.0001737585,0.00008104696,0.0001871998],"domain_scores_gemma":[0.9985762,0.000016936,0.00002781982,0.001243156,0.00006672965,0.00006918958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003667888,0.0001469093,0.002459093,0.00004011031,0.000203663,0.000007072563,0.0005312146,0.01443768,0.9705664,0.001305424,0.004963394,0.005302358],"study_design_scores_gemma":[0.0009200267,0.0005132825,0.05945983,0.00003544543,0.00007843923,0.00009608508,0.0008367548,0.008142457,0.09814639,0.00006070496,0.8308932,0.0008174026],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9585448,0.01465694,0.01228324,0.002731135,0.0004869154,0.0006169496,0.0001398277,0.0006496361,0.009890547],"genre_scores_gemma":[0.989781,0.0006743739,0.007803013,0.0001124041,0.000217902,0.00004056707,0.001060212,0.00003070123,0.0002798014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.87242,"threshold_uncertainty_score":0.4151732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240189912377971,"score_gpt":0.3216540519830536,"score_spread":0.3092521528592739,"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."}}