Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.

Bibliographic Details
Main Author: PLOS ONE Staff
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4361672?pdf=render
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author PLOS ONE Staff
author_facet PLOS ONE Staff
author_sort PLOS ONE Staff
collection DOAJ
first_indexed 2024-12-14T13:22:13Z
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issn 1932-6203
language English
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spelling doaj.art-0deb9725861543099d3c9d82e5fbc08b2022-12-21T22:59:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01103e011974010.1371/journal.pone.0119740Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.PLOS ONE Staffhttp://europepmc.org/articles/PMC4361672?pdf=render
spellingShingle PLOS ONE Staff
Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.
PLoS ONE
title Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.
title_full Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.
title_fullStr Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.
title_full_unstemmed Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.
title_short Correction: predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.
title_sort correction predicting in vitro rumen vfa production using cncps carbohydrate fractions with multiple linear models and artificial neural networks
url http://europepmc.org/articles/PMC4361672?pdf=render
work_keys_str_mv AT plosonestaff correctionpredictinginvitrorumenvfaproductionusingcncpscarbohydratefractionswithmultiplelinearmodelsandartificialneuralnetworks