{"id":"W4232445201","doi":"10.1038/s41580-020-00304-y","title":"Publisher Correction: Applications of CRISPR–Cas in agriculture and plant biotechnology","year":2020,"lang":"en","type":"review","venue":"Nature Reviews Molecular Cell Biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"","keywords":"CRISPR; Biotechnology; Agriculture; Computational biology; Agricultural biotechnology; Biology; Genetics; Gene; Ecology","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":[0.003749799,0.001614399,0.001745059,0.003945238,0.001570966,0.003620676,0.003445285,0.004186301,0.05479245],"category_scores_gemma":[0.01834031,0.000612467,0.0009711818,0.002932367,0.001946978,0.002579492,0.002202972,0.005837088,0.03743906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002254077,"about_ca_system_score_gemma":0.005176458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004591185,"about_ca_topic_score_gemma":0.007952957,"domain_scores_codex":[0.9970464,0.000436294,0.0004248471,0.0003153518,0.001564771,0.0002124364],"domain_scores_gemma":[0.9894629,0.001915841,0.0005322265,0.0008599131,0.006512859,0.0007161918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003018373,0.000005050142,0.00001997886,0.0005898845,0.00001059238,0.0001632894,0.00001771856,0.00004342189,0.000185957,0.001673576,0.9521635,0.04509683],"study_design_scores_gemma":[0.00001255146,0.00001037685,0.000103305,0.0002460621,0.00001293225,0.0004034796,0.00001051094,0.00002720651,0.0002472049,0.0007438996,0.9981729,0.000009547542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001244778,0.0321586,0.001925329,0.02697788,0.9269567,0.00003877973,0.0006732334,0.0004557512,0.01068939],"genre_scores_gemma":[0.009953129,0.1453923,0.009931186,0.05488447,0.2691947,0.00024901,0.003593724,0.001828225,0.5049732],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.05479245,"threshold_uncertainty_score":0.183299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007342585220813724,"score_gpt":0.3200395069437431,"score_spread":0.3126969217229294,"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."}}