A hierarchical class-based machine learning approach for on-site detection of explosives and precursors using NIR spectroscopy.
- DOI
- 10.1016/j.forsciint.2026.113173
- Published
- 2026 Oct 20
- Container
- Forensic science international
- 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.forsciint.2026.113173,
title = {A hierarchical class-based machine learning approach for on-site detection of explosives and precursors using NIR spectroscopy.},
author = {Rais AF and Simoens B and Delémont O},
year = {2026},
journal = {Forensic science international},
doi = {10.1016/j.forsciint.2026.113173},
url = {https://doi.org/10.1016/j.forsciint.2026.113173}
}RIS
TY - JOUR TI - A hierarchical class-based machine learning approach for on-site detection of explosives and precursors using NIR spectroscopy. AU - Rais AF AU - Simoens B AU - Delémont O PY - 2026 JO - Forensic science international DO - 10.1016/j.forsciint.2026.113173 UR - https://doi.org/10.1016/j.forsciint.2026.113173 ER -
APA
AF, R., B, S., & O, D. (2026). A hierarchical class-based machine learning approach for on-site detection of explosives and precursors using NIR spectroscopy.. Forensic science international. https://doi.org/10.1016/j.forsciint.2026.113173
Source records
- pubmed · retrieved 2026-11-10T13:43:54.999Z
- europe-pmc · retrieved 2026-11-10T13:43:55.010Z