reference/36799068

Predicate	Object
contentType	Journal Article
issn	0048-9697
pageRange	170778-
startingPage	170778
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bibliographicCitation	Zhang L, Heuvelink GBM, Mulder VL, Chen S, Deng X, Yang L. Using process-oriented model output to enhance machine learning-based soil organic carbon prediction in space and time. Sci Total Environ. 2024 Feb 08;922():170778. doi: 10.1016/j.scitotenv.2024.170778. PMID: 38336059.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f749cfdca0d90dd1b6d4e4932dc98ecc http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_9e7289d6492140de66d99c5e01bf9150 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_944e62554d041f464ea897e5994c1a1f http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_0b0be20df13c04ac7377a88bada21673 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_32d3adc18ad20bcd6614dc65367fdffa http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_e659e70f32a94d5dab44a36f9e0ef203
date	2024-02-08-04:00^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://doi.org/10.1016/j.scitotenv.2024.170778 https://pubmed.ncbi.nlm.nih.gov/38336059
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language	English
source	https://www.crossref.org/ https://pubmed.ncbi.nlm.nih.gov/
title	Using process-oriented model output to enhance machine learning-based soil organic carbon prediction in space and time

Total number of triples: 21.