{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008583234,0.001170325,0.001083148,0.00124399,0.0006169287,0.001238265,0.001360964,0.001267971,0.002735299],"category_scores_gemma":[0.0009413227,0.0008189353,0.000544033,0.0009132174,0.0006999419,0.0007408931,0.0009787118,0.002754082,0.003514623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006111484,"about_ca_system_score_gemma":0.0006656604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006491226,"about_ca_topic_score_gemma":0.001406054,"domain_scores_codex":[0.998619,0.0001889682,0.0001500671,0.0003649286,0.0005829171,0.00009404166],"domain_scores_gemma":[0.9993501,0.0001494487,0.000190391,0.0001330229,0.00008550013,0.00009144403],"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":[0.00005054384,0.00002725869,0.0001567576,0.0001850932,0.00002000893,0.0001142343,0.00002618766,0.0001613911,0.985499,0.0009270406,0.001255971,0.01157659],"study_design_scores_gemma":[0.000009128673,0.00005012446,0.0004692656,0.00001665674,0.00001792814,0.0006959772,0.000009063587,0.001318691,0.9662352,0.0002835538,0.03087332,0.00002117769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07399727,0.005727442,0.8964343,0.0009474455,0.000497815,0.0006117305,0.004225451,0.008958696,0.008599751],"genre_scores_gemma":[0.2643902,0.007682585,0.6941657,0.0006134926,0.0001586747,0.0006942255,0.01029352,0.001488334,0.02051318],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002735299,"threshold_uncertainty_score":0.009150445,"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."}}