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:	1765
	Name:	1-(5-acetyl-2,6-dimethylpyridin-3-yl)ethan-1-one
	Description:
	Labels:	Neutral
	CAS:	24234-61-5
	InChi Code:	InChI=1/C11H13NO2/c1-6-10(8(3)13)5-11(9(4)14)7(2)12-6/h5H,1-4H3

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

Value	Source or prediction
-0.54	experimental value
-0.08	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
0.87	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
-0.53	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
-0.23	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
0.12	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
0.56	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
-0.47	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
0.88	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
-0.52	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
-0.01	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
-0.61	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
-0.02	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)