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农药对. 的自洽模型系统。

The system of self-consistent models for pesticide toxicity to .

机构信息

Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy.

出版信息

Toxicol Mech Methods. 2023 Sep;33(7):578-583. doi: 10.1080/15376516.2023.2197487. Epub 2023 May 8.

Abstract

Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool of modern theoretical and computational chemistry. The self-consistent model system is both a method to build up a group of QSPR/QSAR models and an approach to checking the reliability of these models. Here, a group of models of pesticide toxicity toward for different distributions into training and test sub-sets is compared. This comparison is the basis for formulating the system of self-consistent models. The so-called index of the ideality of correlation () has been used to improve the above models' predictive potential of pesticide toxicity. The predictive potential of the suggested models should be classified as high since the average value of the determination coefficient for the validation sets is 0.841, and the dispersion is 0.033 (on all five models). The best model (number 4) has an average determination coefficient of 0.89 for the external validation sets (related to all five splits).

摘要

定量构效关系(QSARs)是现代理论和计算化学的工具。自洽模型系统既是构建一组 QSPR/QSAR 模型的方法,也是检查这些模型可靠性的方法。在这里,比较了不同分布的一组农药对 的毒性模型,将其分为训练和测试子集。这种比较是制定自洽模型系统的基础。所谓的相关理想指数()已被用于提高上述模型对农药毒性的预测能力。由于验证集的确定系数的平均值为 0.841,分散度为 0.033(在所有五个模型上),因此所提出模型的预测能力应归类为高。最佳模型(第 4 号)对外部验证集(与所有五个拆分相关)的平均确定系数为 0.89。

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