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:	1823
	Name:	1-(isothiocyanatomethyl)naphthalene
	Description:
	Labels:	Neutral
	CAS:	17112-82-2
	InChi Code:	InChI=1/C12H9NS/c14-9-13-8-11-6-3-5-10-4-1-2-7-12(10)11/h1-7H,8H2

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

Value	Source or prediction
3.05	experimental value
2.69	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
2.15	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
3.04	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
2.58	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
2.58	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
2.41	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
2.96	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
2.54	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
2.72	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
2.57	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
2.99	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
2.28	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)