Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data
- DOI
- 10.1021/acsomega.4c09719
- Published
- 2025-01-30
- Container
- ACS Omega
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acsomega.4c09719,
title = {Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data},
author = {Mihkel Kotli and Geven Piir and Uko Maran},
year = {2025},
journal = {ACS Omega},
doi = {10.1021/acsomega.4c09719},
url = {https://doi.org/10.1021/acsomega.4c09719}
}RIS
TY - JOUR TI - Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data AU - Mihkel Kotli AU - Geven Piir AU - Uko Maran PY - 2025 JO - ACS Omega DO - 10.1021/acsomega.4c09719 UR - https://doi.org/10.1021/acsomega.4c09719 ER -
APA
Kotli, M., Piir, G., & Maran, U. (2025). Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data. ACS Omega. https://doi.org/10.1021/acsomega.4c09719
Source records
- crossref · retrieved 2026-09-25T08:49:38.282Z