{"id":"W4409031076","doi":"10.3389/fgeed.2025.1565297","title":"Cas9 endonuclease: a molecular tool for in vitro cloning and CRISPR edit detection","year":2025,"lang":"en","type":"article","venue":"Frontiers in Genome Editing","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Calgary; University of Saskatchewan; Saskatchewan Research Council (Canada)","funders":"Saskatchewan Wheat Development Commission; Genome Prairie; Agriculture and Agri-Food Canada; Western Grains Research Foundation; Genome Canada; Alberta Wheat Commission; Ministry of Agriculture - Saskatchewan","keywords":"CRISPR; Endonuclease; Computational biology; Cloning (programming); Cas9; Biology; Genetics; Genome editing; Molecular biology; DNA; Computer science; Gene; Programming language","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":[0.0002297195,0.0001252928,0.0001499518,0.0001682882,0.00005144611,0.0000249008,0.00008091044,0.0001211106,7.797286e-7],"category_scores_gemma":[0.0001960661,0.0001551054,0.00004557996,0.0001349061,0.00002421124,0.00000461161,0.0000677987,0.0001120583,1.478105e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004348735,"about_ca_system_score_gemma":0.00002301974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001661728,"about_ca_topic_score_gemma":0.00001313319,"domain_scores_codex":[0.9991256,0.00002046106,0.0002098691,0.0003109885,0.00005374989,0.0002793081],"domain_scores_gemma":[0.9997605,0.0000137169,0.00003390621,0.0001356503,0.00002599015,0.00003022285],"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":[0.00006945447,0.00001101759,0.001377421,0.00007956167,0.00002140533,0.000006898035,0.00007349016,0.001287382,0.9814824,0.000006912308,0.0003200137,0.01526405],"study_design_scores_gemma":[0.001167252,0.00006516744,0.002610896,0.00004594889,0.00001992248,0.000006607193,0.0005362807,0.005573449,0.9655082,0.0001620303,0.02406032,0.0002439963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5827184,0.004050795,0.4114099,0.00005471439,0.001332616,0.0002675538,0.00001179527,0.00001092574,0.0001433885],"genre_scores_gemma":[0.9813061,0.00007779396,0.01780073,0.00008092426,0.000526921,0.00008235944,0.00003897068,0.00001930634,0.00006690889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3985877,"threshold_uncertainty_score":0.6325015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002530670746190941,"score_gpt":0.246183124449879,"score_spread":0.2436524537036881,"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."}}