{"id":"W4409537694","doi":"10.1038/s41587-025-02674-0","title":"Author Correction: Precise, predictable multi-nucleotide deletions in rice and wheat using APOBEC–Cas9","year":2025,"lang":"en","type":"erratum","venue":"Nature Biotechnology","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"","keywords":"APOBEC; Genetics; Biology; Nucleotide; Computational biology; Gene; Genome","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001659068,0.0003495654,0.0004103288,0.0004183631,0.0002102519,0.00004204068,0.0003547963,0.005325793,0.00002049592],"category_scores_gemma":[0.000329219,0.0003587155,0.0000930359,0.0003298573,0.000172691,0.000003867992,0.0004514582,0.001854543,0.000003776342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004810773,"about_ca_system_score_gemma":0.0002113431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002167419,"about_ca_topic_score_gemma":0.0004779405,"domain_scores_codex":[0.9982928,0.00006066676,0.0002792449,0.0008253045,0.000130577,0.0004113897],"domain_scores_gemma":[0.9992083,0.00002004933,0.000138173,0.0004594128,0.0001025405,0.00007156879],"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":[0.00005560474,0.000106082,0.000580722,0.0001426862,0.00009461834,0.00002383867,0.00001824511,0.00003796572,0.03844029,0.00007136422,0.9586552,0.001773416],"study_design_scores_gemma":[0.0005314691,0.0001626449,0.0009762699,0.0002987739,0.00007636823,0.00009648754,0.0001313319,0.001331494,0.00793048,0.00003359559,0.9880334,0.0003977594],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.3261517,0.3069685,0.01826529,0.02184234,0.2226505,0.005821853,0.005016915,0.001382302,0.09190065],"genre_scores_gemma":[0.1281143,0.02273054,0.01359984,0.001400329,0.002159715,0.00005576376,0.002630333,0.0001081898,0.8292009],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7373003,"threshold_uncertainty_score":0.9998865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156857984748676,"score_gpt":0.2627474504952989,"score_spread":0.2511788706478121,"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."}}