{"id":"W4212872437","doi":"10.1186/s12896-022-00737-7","title":"An efficient and specific CRISPR-Cas9 genome editing system targeting soybean phytoene desaturase genes","year":2022,"lang":"en","type":"article","venue":"BMC Biotechnology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Biology; Phytoene desaturase; CRISPR; Genome editing; Gene; Cas9; Genetics; Genome; Computational biology; Gene silencing","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":[0.0003032796,0.0002172691,0.0001986337,0.0001434775,0.0003523412,0.00002795683,0.0003074059,0.000223516,0.00001857337],"category_scores_gemma":[0.00002385395,0.0002380645,0.00006255889,0.0001782707,0.00009973644,0.000002305715,0.0004144454,0.0002505424,0.000003925231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004163958,"about_ca_system_score_gemma":0.00002816962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001184169,"about_ca_topic_score_gemma":0.00001124684,"domain_scores_codex":[0.9984919,0.00007127049,0.0002637998,0.0006133782,0.0001309061,0.0004287277],"domain_scores_gemma":[0.999298,0.00001017217,0.00008901481,0.0004826356,0.00003137288,0.00008881876],"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":[0.00002619774,0.00003975155,0.0006916636,0.00005832041,0.00001754649,0.00001651832,0.00004240667,0.01263691,0.98448,0.0003709525,0.0001036848,0.001516089],"study_design_scores_gemma":[0.0006786115,0.0005102482,0.001548779,0.00001032658,0.00002613253,0.0004131876,0.004200518,0.01178122,0.9405982,0.00001071821,0.03969744,0.0005246345],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8890955,0.01090867,0.0989558,0.00009268179,0.0004675136,0.0002261264,0.00004361592,0.0001631248,0.00004695824],"genre_scores_gemma":[0.9847572,0.0001214629,0.01436905,0.00003511197,0.0004760766,0.00005279077,0.0001196587,0.00004471741,0.00002394377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09566168,"threshold_uncertainty_score":0.970799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007166046550000191,"score_gpt":0.2444570798837921,"score_spread":0.2372910333337919,"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."}}