Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.
- DOI
- 10.1007/s10653-024-02087-z
- Published
- 2024 Jul 13
- Container
- Environmental geochemistry and health
- Publisher
- Not recorded
- Open access
- unknown
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.
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Cite this work
BibTeX
@article{allodium:10.1007/s10653-024-02087-z,
title = {Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.},
author = {Li C and Jiang Z and Li W and Yu T and Wu X and Hu Z and Yang Y and Yang Z and Xu H and Zhang W and Zhang W and Ye Z},
year = {2024},
journal = {Environmental geochemistry and health},
doi = {10.1007/s10653-024-02087-z},
url = {https://doi.org/10.1007/s10653-024-02087-z}
}RIS
TY - JOUR TI - Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area. AU - Li C AU - Jiang Z AU - Li W AU - Yu T AU - Wu X AU - Hu Z AU - Yang Y AU - Yang Z AU - Xu H AU - Zhang W AU - Zhang W AU - Ye Z PY - 2024 JO - Environmental geochemistry and health DO - 10.1007/s10653-024-02087-z UR - https://doi.org/10.1007/s10653-024-02087-z ER -
APA
C, L., Z, J., W, L., T, Y., X, W., Z, H., Y, Y., Z, Y., H, X., W, Z., W, Z., & Z, Y. (2024). Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.. Environmental geochemistry and health. https://doi.org/10.1007/s10653-024-02087-z
Source records
- pubmed · retrieved 2026-09-27T07:01:33.672Z