Correction to Impact of multi-output and stacking methods on feed efficiency prediction from genotype using machine learning algorithms

IF 1.9 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE
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引用次数: 0

Abstract

Mora M, González P, Quevedo JR, Montañés E, Tusell L, Bergsma R, Piles M. Impact of multi-output and stacking methods on feed efficiency prediction from genotype using machine learning algorithms. J Anim Breed Genet. 2023 Nov;140(6):638–652. doi: 10.1111/jbg.12815. PMID: 37403756.

The text in the funding section in the published article is incorrect; the correct text is shown below.

This work received funding for open access charge: CRUE-Universitat Politècnica de València. MM is a recipient of a ‘Formación de Personal Investigador (FPI)’ associated with the research project RTI2018-097610R-I00. This research was also supported by the project PID2021-128173OR-C21 (GENEF3) (grant no. PID2019-110742RB-I00).

We apologize for this error.

更正 "多输出和堆叠方法对使用机器学习算法从基因型预测饲料效率的影响"。
Mora M、González P、Quevedo JR、Montañés E、Tusell L、Bergsma R、Piles M.多输出和堆叠方法对使用机器学习算法从基因型预测饲料效率的影响。J Anim Breed Genet.doi: 10.1111/jbg.12815.PMID: 37403756.已发表文章中资助部分的文字有误,正确文字如下:CRUE-Universitat Politècnica de València.MM 是与研究项目 RTI2018-097610R-I00 相关的 "个人研究员培养计划(FPI)"的获得者。本研究还得到了 PID2021-128173OR-C21 (GENEF3) 项目的支持(赠款编号:PID2019-110742RB-I00)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Animal Breeding and Genetics
Journal of Animal Breeding and Genetics 农林科学-奶制品与动物科学
CiteScore
5.20
自引率
3.80%
发文量
58
审稿时长
12-24 weeks
期刊介绍: The Journal of Animal Breeding and Genetics publishes original articles by international scientists on genomic selection, and any other topic related to breeding programmes, selection, quantitative genetic, genomics, diversity and evolution of domestic animals. Researchers, teachers, and the animal breeding industry will find the reports of interest. Book reviews appear in many issues.
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