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:	1739
	Name:	1-isothiocyanatonaphthalene
	Description:
	Labels:	Neutral
	CAS:	551-06-4
	InChi Code:	InChI=1/C11H7NS/c13-8-12-11-7-3-5-9-4-1-2-6-10(9)11/h1-7H

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

Value	Source or prediction
2.14	experimental value
2.23	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
2.2	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
2.15	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
2.57	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
2.56	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
2.83	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
2.15	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
2.5	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
2.34	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
3.0	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
2.22	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
3.21	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)