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Updated: Jan 9, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
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一种基于定量离子特征-活性关系 (QICAR) 的新方法来预测大米中的生物度因子,加上可解释的机器学习

Yifei Gao1, Wenhao Zhao2, Xuedong Wang3

  • 1State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.

The Science of the total environment
|December 1, 2025
PubMed
概括

这项研究引入了一种新的定量离子特性-活性关系 (QICAR) 模型,用于预测大米中的重金属积累. 该模型使用土壤和金属特性准确预测生物度因子,增强食品安全评估.

关键词:
生物度因子生物度因子机器学习是机器学习.在QICAR QICAR中使用.大米 大米 大米 大米 大米软度指数是一个软度指数.

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