Quantifying environment-dependent global antibiotic resistance gene risk patterns and mitigation scenarios using integrated machine learning and counterfactual scenario evaluation
- DOI
- 10.1016/j.jenvman.2026.131232
- Published
- 2026-11
- Container
- Journal of Environmental Management
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jenvman.2026.131232,
title = {Quantifying environment-dependent global antibiotic resistance gene risk patterns and mitigation scenarios using integrated machine learning and counterfactual scenario evaluation},
author = {Hanshu Zhang and Yongpeng Zhang and Jianqiang Su and Yiliang He and Peng Li and Bo Zhang},
year = {2026},
journal = {Journal of Environmental Management},
doi = {10.1016/j.jenvman.2026.131232},
url = {https://doi.org/10.1016/j.jenvman.2026.131232}
}RIS
TY - JOUR TI - Quantifying environment-dependent global antibiotic resistance gene risk patterns and mitigation scenarios using integrated machine learning and counterfactual scenario evaluation AU - Hanshu Zhang AU - Yongpeng Zhang AU - Jianqiang Su AU - Yiliang He AU - Peng Li AU - Bo Zhang PY - 2026 JO - Journal of Environmental Management DO - 10.1016/j.jenvman.2026.131232 UR - https://doi.org/10.1016/j.jenvman.2026.131232 ER -
APA
Zhang, H., Zhang, Y., Su, J., He, Y., Li, P., & Zhang, B. (2026). Quantifying environment-dependent global antibiotic resistance gene risk patterns and mitigation scenarios using integrated machine learning and counterfactual scenario evaluation. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2026.131232
Source records
- crossref · retrieved 2026-11-11T01:20:38.290Z