Green credit risk assessment and prediction in China's construction industry: based on the optuna-catboost model.

Qin Z, Meng M, Li D, Li J

Open source

DOI: 10.1038/s41598-026-56704-1
Published: 2026 Jun 5
Container: Scientific reports
Publisher: Not recorded
Open access: yes

Credibility signals

uncertain Score 53/100 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. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. 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
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
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
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-56704-1,
  title = {Green credit risk assessment and prediction in China's construction industry: based on the optuna-catboost model.},
  author = {Qin Z and Meng M and Li D and Li J},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-56704-1},
  url = {https://doi.org/10.1038/s41598-026-56704-1}
}

RIS

TY  - JOUR
TI  - Green credit risk assessment and prediction in China's construction industry: based on the optuna-catboost model.
AU  - Qin Z
AU  - Meng M
AU  - Li D
AU  - Li J
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-56704-1
UR  - https://doi.org/10.1038/s41598-026-56704-1
ER  -

APA

Z, Q., M, M., D, L., & J, L. (2026). Green credit risk assessment and prediction in China's construction industry: based on the optuna-catboost model.. Scientific reports. https://doi.org/10.1038/s41598-026-56704-1

Source records

pubmed · retrieved 2026-11-10T14:13:57.249Z
europe-pmc · retrieved 2026-11-10T14:13:57.259Z
doaj · retrieved 2026-11-10T14:13:57.249Z