{"id":"W3181953750","doi":"10.1016/j.molp.2021.07.010","title":"Highly efficient heritable genome editing in wheat using an RNA virus and bypassing tissue culture","year":2021,"lang":"en","type":"article","venue":"Molecular Plant","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":191,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"Youth Innovation Promotion Association of the Chinese Academy of Sciences; Chinese Universities Scientific Fund; Chinese Academy of Sciences; China Agricultural University; National Natural Science Foundation of China","keywords":"Biology; Genome editing; Cas9; Genome; Mutagenesis; Transformation (genetics); Transgene; Genetics; CRISPR; Virus; Brome mosaic virus; Mutant; Genetically modified crops; Gene; Computational biology; RNA; RNA-dependent RNA polymerase","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":[],"consensus_categories":[],"category_scores_codex":[0.0001053107,0.0001572107,0.0001482377,0.00003766343,0.00006859772,0.0000616098,0.00007368582,0.0001237013,0.000006271619],"category_scores_gemma":[0.00002452865,0.0001675142,0.00002538429,0.00009549638,0.00002185423,0.000003512021,0.0001013507,0.0001036328,0.000001041474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002048113,"about_ca_system_score_gemma":0.00004249926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000580568,"about_ca_topic_score_gemma":0.00007691712,"domain_scores_codex":[0.9990138,0.00004631924,0.0001642792,0.0003741614,0.0001097347,0.0002917525],"domain_scores_gemma":[0.9996173,0.000002902012,0.00002758962,0.0002201435,0.00003391203,0.00009814186],"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":[0.000007301976,0.00004026144,0.00004361368,0.00002730278,0.00001391156,0.0002586405,0.0001557898,0.02954485,0.9694487,0.00001317382,0.00001540857,0.0004309831],"study_design_scores_gemma":[0.0003300849,0.00006715336,0.0002955396,0.00003877038,0.00001560476,0.0002124433,0.0001804632,0.005886842,0.9875498,0.000006641504,0.005199246,0.0002173712],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631884,0.007258676,0.02904353,0.00003215027,0.0001299938,0.00008487984,0.00003499509,0.00001198287,0.0002153967],"genre_scores_gemma":[0.9939294,0.0001010093,0.005395226,0.0001144764,0.0001600696,0.000004599185,0.0002129991,0.00002732155,0.0000548243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03074108,"threshold_uncertainty_score":0.683103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007126271313292723,"score_gpt":0.2611605942296268,"score_spread":0.254034322916334,"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."}}