{"id":"W4323363119","doi":"10.21203/rs.3.rs-2625838/v1","title":"PAM-Flexible Genome Editing with an Engineered Chimeric Cas9","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Cas9; Genome editing; CRISPR; Computational biology; Genome engineering; Limiting; Protein engineering; Genome; Biology; Computer science; Flexibility (engineering); Genetics; Enzyme; Gene; Engineering; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007653268,0.0003207973,0.0002719065,0.0003129956,0.0001555432,0.0001281622,0.0005352427,0.0003813006,0.0000403755],"category_scores_gemma":[0.0001630162,0.0003041603,0.0001087832,0.0003645612,0.00009206847,0.000003506779,0.0009259016,0.0009111292,0.00005122874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005247982,"about_ca_system_score_gemma":0.0002709434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002159784,"about_ca_topic_score_gemma":0.0001331302,"domain_scores_codex":[0.9973326,0.000125016,0.0002364773,0.0008687598,0.0006103191,0.000826852],"domain_scores_gemma":[0.998228,0.00003218805,0.00004793023,0.00107734,0.0003280312,0.0002865126],"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":[0.0004775398,0.0003956553,0.003827862,0.004683028,0.0009585434,0.0005207334,0.001361116,0.3321484,0.6409442,0.0001234029,0.005572601,0.008986895],"study_design_scores_gemma":[0.00443206,0.01078757,0.09745117,0.00278231,0.0002317768,0.0003288248,0.006891914,0.0250979,0.6339462,0.0009659851,0.2107977,0.006286642],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654378,0.003582615,0.02610768,0.0003234613,0.0006406107,0.001469646,0.0003743921,0.000331092,0.001732717],"genre_scores_gemma":[0.9906204,0.0008160269,0.002221393,0.00001338365,0.002240003,0.0002728846,0.001880368,0.0001736814,0.001761905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3070505,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04928726360684882,"score_gpt":0.4087015400650201,"score_spread":0.3594142764581713,"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."}}