Spatial modeling of impervious surface effects on thermal gradients in arid urban neighborhoods using geographically neural network weighted regression (Gnnwr)
- DOI
- 10.6084/m9.figshare.32888483.v1
- Published
- 2026
- Container
- Not recorded
- Publisher
- Taylor & Francis
- Open access
- yes
Credibility signals
limited evidence Score 47/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- 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.
- supportingOpen access status: Normalized open-access status: open.
- supportingPublication license: A publication license was supplied: https://creativecommons.org/licenses/by/4.0/legalcode. Presence improves reuse transparency, not research validity.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.6084/m9.figshare.32888483.v1,
title = {Spatial modeling of impervious surface effects on thermal gradients in arid urban neighborhoods using geographically neural network weighted regression (Gnnwr)},
author = {Shawky Mansour and Abdullatif Alyaqout and Meshari Alenezi},
year = {2026},
doi = {10.6084/m9.figshare.32888483.v1},
url = {https://doi.org/10.6084/m9.figshare.32888483.v1}
}RIS
TY - JOUR TI - Spatial modeling of impervious surface effects on thermal gradients in arid urban neighborhoods using geographically neural network weighted regression (Gnnwr) AU - Shawky Mansour AU - Abdullatif Alyaqout AU - Meshari Alenezi PY - 2026 DO - 10.6084/m9.figshare.32888483.v1 UR - https://doi.org/10.6084/m9.figshare.32888483.v1 ER -
APA
Mansour, S., Alyaqout, A., & Alenezi, M. (2026). Spatial modeling of impervious surface effects on thermal gradients in arid urban neighborhoods using geographically neural network weighted regression (Gnnwr). https://doi.org/10.6084/m9.figshare.32888483.v1
Source records
- datacite · retrieved 2026-09-25T19:58:19.916Z