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:	1875
	Name:	(1S,2R,4S)-1,7,7-trimethylbicyclo[2.2.1]heptan-2-yl acetate
	Description:
	Labels:	Neutral
	CAS:	5655-61-8
	InChi Code:	InChI=1/C12H20O2/c1-8(13)14-10-7-9-5-6-12(10,4)11(9,2)3/h9-10H,5-7H2,1-4H3/t9-,10+,12+/m0/s1

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

Value	Source or prediction
0.68	experimental value
0.68	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
0.63	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
0.67	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
0.41	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
0.24	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
0.42	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
0.64	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
0.57	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
0.67	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
0.31	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)
0.32	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)