Global patterns and key drivers of stream nitrogen concentration: A machine learning approach
- DOI
- 10.1016/j.scitotenv.2023.161623
- Published
- 2023-04
- Container
- Science of The Total Environment
- Publisher
- Elsevier BV
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1016/j.scitotenv.2023.161623,
title = {Global patterns and key drivers of stream nitrogen concentration: A machine learning approach},
author = {Razi Sheikholeslami and Jim W. Hall},
year = {2023},
journal = {Science of The Total Environment},
doi = {10.1016/j.scitotenv.2023.161623},
url = {https://doi.org/10.1016/j.scitotenv.2023.161623}
}RIS
TY - JOUR TI - Global patterns and key drivers of stream nitrogen concentration: A machine learning approach AU - Razi Sheikholeslami AU - Jim W. Hall PY - 2023 JO - Science of The Total Environment DO - 10.1016/j.scitotenv.2023.161623 UR - https://doi.org/10.1016/j.scitotenv.2023.161623 ER -
APA
Sheikholeslami, R., & Hall, J. W. (2023). Global patterns and key drivers of stream nitrogen concentration: A machine learning approach. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2023.161623
Source records
- crossref · retrieved 2026-09-27T11:02:05.723Z