Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training set | training | 36 | 0.929 | 0.150 |
When using this QDB archive, please cite (see details) it together with the original article:
Piir, G. Data for: Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. QsarDB repository, QDB.190. 2017. https://doi.org/10.15152/QDB.190
Zhang, C.; Feng, L.; Wei, J. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. Chin. Sci. Bull. 2002, 47, 1270. https://doi.org/10.1360/02tb9281
Title: | Zhang, C.; Feng, L.; Wei, J. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. Chin. Sci. Bull. 2002, 47, 1270. |
Abstract: | Based on theoretical linear solvation energy relationship and quantum chemical descriptors computed by AM1 Hamiltonian, a new model is developed to predict the partitioning of some volatile organic compounds between the plant cuticular matrix and air. |
URI: | http://hdl.handle.net/10967/190
http://dx.doi.org/10.15152/QDB.190 |
Date: | 2017-03-23 |
Name | Description | Format | Size | View |
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2002CSB1270.qdb.zip | Model for volatile organic compounds | application/zip | 7.468Kb | View/ |