Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924.

Compound

	ID:	1766
	Name:	3,4-diethyl pyridine-3,4-dicarboxylate
	Description:
	Labels:	Neutral
	CAS:	1678-52-0
	InChi Code:	InChI=1/C11H13NO4/c1-3-15-10(13)8-5-6-12-7-9(8)11(14)16-4-2/h5-7H,3-4H2,1-2H3

pIGC50: 40-h Tetrahymena toxicity as log(1/IGC50) [log(L/mmol)] i

Value	Source or prediction
-0.13	experimental value
0.03	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
0.47	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
-0.14	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
-0.26	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
0.34	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
0.22	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
-0.17	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
0.33	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
-0.02	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
-0.09	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
-0.09	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
-0.16	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)