Hybrid data-driven machine learning model for predicting performance of lignocellulosic biomass gasification.
- DOI
- 10.1016/j.biortech.2026.134001
- Published
- 2026 Mar
- Container
- Bioresource technology
- Publisher
- Not recorded
- Open access
- no
Credibility signals
limited evidence Score 43/100 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.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.biortech.2026.134001,
title = {Hybrid data-driven machine learning model for predicting performance of lignocellulosic biomass gasification.},
author = {Santana HEP and Ruzene DS and Silva IP and Silva DP},
year = {2026},
journal = {Bioresource technology},
doi = {10.1016/j.biortech.2026.134001},
url = {https://doi.org/10.1016/j.biortech.2026.134001}
}RIS
TY - JOUR TI - Hybrid data-driven machine learning model for predicting performance of lignocellulosic biomass gasification. AU - Santana HEP AU - Ruzene DS AU - Silva IP AU - Silva DP PY - 2026 JO - Bioresource technology DO - 10.1016/j.biortech.2026.134001 UR - https://doi.org/10.1016/j.biortech.2026.134001 ER -
APA
HEP, S., DS, R., IP, S., & DP, S. (2026). Hybrid data-driven machine learning model for predicting performance of lignocellulosic biomass gasification.. Bioresource technology. https://doi.org/10.1016/j.biortech.2026.134001
Source records
- pubmed · retrieved 2026-09-27T06:25:18.680Z
- europe-pmc · retrieved 2026-09-27T06:25:18.687Z