{"id":"W4240274708","doi":"10.1093/nar/gky512","title":"Optimized knock-in of point mutations in zebrafish using CRISPR/Cas9","year":2018,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Appili Therapeutics (Canada); McMaster University; Dalhousie University","funders":"","keywords":"CRISPR; Biology; Cas9; Zebrafish; Genetics; Gene knockin; Point mutation; Computational biology; Palindrome; Genome editing; Polymerase chain reaction; Mutation; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005837095,0.0007427775,0.0005380908,0.0004600085,0.0003731044,0.0004409699,0.0005607589,0.0004559287,0.001458462],"category_scores_gemma":[0.0003081532,0.0003523617,0.0005186064,0.0002052494,0.0004262599,0.0003005926,0.0004455702,0.0009966969,0.0006320275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005414286,"about_ca_system_score_gemma":0.000708341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00182181,"about_ca_topic_score_gemma":0.005401879,"domain_scores_codex":[0.9995527,0.00003710274,0.00007918422,0.0001054044,0.0001746039,0.00005101729],"domain_scores_gemma":[0.9997823,0.00003764137,0.00006389702,0.00004227695,0.00004293993,0.00003104484],"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":[0.00001989412,0.00001321231,0.00009336703,0.00003435417,0.000006557058,0.00006843201,0.00001178518,0.0003549891,0.9976153,0.0002288382,0.000053784,0.001499545],"study_design_scores_gemma":[0.00001099372,0.00008935655,0.0006169708,0.000006399569,0.0000198584,0.0001380796,0.000008648514,0.001203042,0.9953001,0.00007637322,0.002516073,0.00001406891],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7548097,0.00124127,0.2305388,0.0003210577,0.0002077621,0.0009559817,0.00311673,0.002699726,0.006109001],"genre_scores_gemma":[0.7493948,0.001389051,0.2364099,0.0001537627,0.00001837341,0.0005031406,0.002171894,0.0005734611,0.009385631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00182181,"threshold_uncertainty_score":0.004879057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03848736674112608,"score_gpt":0.4032562825176894,"score_spread":0.3647689157765633,"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."}}