Pathways, evidence types, and interpretive boundaries in machine learning-assisted source analysis of soil metal(loid)s
- DOI
- 10.1016/j.jhazmat.2026.143727
- Published
- 2026-10
- Container
- Journal of Hazardous Materials
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jhazmat.2026.143727,
title = {Pathways, evidence types, and interpretive boundaries in machine learning-assisted source analysis of soil metal(loid)s},
author = {Quan Zou and Yingming Wang and Zhenyang Han and Jie Shi and Weijie Cao and Jiayi Luo and Xiaodong Yue},
year = {2026},
journal = {Journal of Hazardous Materials},
doi = {10.1016/j.jhazmat.2026.143727},
url = {https://doi.org/10.1016/j.jhazmat.2026.143727}
}RIS
TY - JOUR TI - Pathways, evidence types, and interpretive boundaries in machine learning-assisted source analysis of soil metal(loid)s AU - Quan Zou AU - Yingming Wang AU - Zhenyang Han AU - Jie Shi AU - Weijie Cao AU - Jiayi Luo AU - Xiaodong Yue PY - 2026 JO - Journal of Hazardous Materials DO - 10.1016/j.jhazmat.2026.143727 UR - https://doi.org/10.1016/j.jhazmat.2026.143727 ER -
APA
Zou, Q., Wang, Y., Han, Z., Shi, J., Cao, W., Luo, J., & Yue, X. (2026). Pathways, evidence types, and interpretive boundaries in machine learning-assisted source analysis of soil metal(loid)s. Journal of Hazardous Materials. https://doi.org/10.1016/j.jhazmat.2026.143727
Source records
- crossref · retrieved 2026-09-26T09:22:07.831Z