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:	1615
	Name:	2-hydroxy-1,4-dihydronaphthalene-1,4-dione
	Description:
	Labels:	Neutral
	CAS:	83-72-7
	InChi Code:	InChI=1/C10H6O3/c11-8-5-9(12)10(13)7-4-2-1-3-6(7)8/h1-5,12H

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

Value	Source or prediction
0.8	experimental value
1.01	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
1.31	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
1.04	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
1.94	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
2.11	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
2.28	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
0.96	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
2.32	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
1.31	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
2.13	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
0.7	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
2.17	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)