Improving groundwater quality predictions in semi-arid regions using ensemble learning models

Maedeh Mahmoudi, Amin Mahdavi-Meymand, Ammar AlDallal, Mohammad Zounemat-Kermani

Open source

DOI: 10.1007/s11356-024-35874-3
Published: 2025-01-04
Container: Environmental Science and Pollution Research
Publisher: Springer Science and Business Media LLC
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. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1007/s11356-024-35874-3,
  title = {Improving groundwater quality predictions in semi-arid regions using ensemble learning models},
  author = {Maedeh Mahmoudi and Amin Mahdavi-Meymand and Ammar AlDallal and Mohammad Zounemat-Kermani},
  year = {2025},
  journal = {Environmental Science and Pollution Research},
  doi = {10.1007/s11356-024-35874-3},
  url = {https://doi.org/10.1007/s11356-024-35874-3}
}

RIS

TY  - JOUR
TI  - Improving groundwater quality predictions in semi-arid regions using ensemble learning models
AU  - Maedeh Mahmoudi
AU  - Amin Mahdavi-Meymand
AU  - Ammar AlDallal
AU  - Mohammad Zounemat-Kermani
PY  - 2025
JO  - Environmental Science and Pollution Research
DO  - 10.1007/s11356-024-35874-3
UR  - https://doi.org/10.1007/s11356-024-35874-3
ER  -

APA

Mahmoudi, M., Mahdavi-Meymand, A., AlDallal, A., & Zounemat-Kermani, M. (2025). Improving groundwater quality predictions in semi-arid regions using ensemble learning models. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-024-35874-3

Source records

crossref · retrieved 2026-09-25T06:19:02.967Z