Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 19 | 0.907 | 0.374 |
Validation set | external validation | 10 | 0.885 | 0.453 |
When using this QDB archive, please cite (see details) it together with the original article:
Kahn, I. Data for: Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. QsarDB repository, QDB.145. 2015. https://doi.org/10.15152/QDB.145
Austin, T. J.; Eadsforth, C. V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160. https://doi.org/10.1080/1062936x.2013.871577
dc.date.accessioned | 2015-03-31T20:00:15Z | |
dc.date.available | 2015-03-31T20:00:15Z | |
dc.date.issued | 2015-03-31 | * |
dc.identifier.uri | http://hdl.handle.net/10967/145 | |
dc.identifier.uri | http://dx.doi.org/10.15152/QDB.145 | |
dc.description.abstract | To comply with the REACH (Registration, Evaluation, Authorisation and restriction of Chemicals) regulations, the generation of chronic fish toxicity data is required for chemicals produced or imported within or into the EU in quantities greater than 100 tonnes per year. This comes at a great cost to industry and consumers alike and requires the sacrifice of many vertebrates. In acknowledgment of these issues the REACH regulations encourage the use of non-testing methods (NTM). These include read-across, weight-of-evidence and QSAR (quantitative structure–activity relationship) techniques. There are many QSAR tools available to generate predictive values for a number of physico-chemical properties, as well as human and environmental health end points; however, close analysis of the currently available chronic fish models identified room for improvement in both the selection of data used and in its application in model creation. In light of this a model was developed using only sub-lethal no-observed-effect concentration (NOEC) end-point data according to best practice QSAR development. Only the lowest value was taken for each compound, in line with the conservative approach taken by the European Chemicals Agency (ECHA). The model developed meets the Organisation for Economic Co-operation and Development (OECD) principles, has strong internal and external validation statistics, and can reliably predict sub-lethal chronic NOEC values for fish within its defined applicability domain. | |
dc.publisher | Iiris Kahn | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.title | Austin, T.J.; Eadsforth, C.V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160. | |
qdb.property.endpoint | 3. Ecotoxic effects 3.5. Long-term toxicity to fish | en_US |
qdb.prediction.application | Minitab 16 | en_US |
bibtex.entry | article | en_US |
bibtex.entry.author | Austin, T. J. | |
bibtex.entry.author | Eadsforth, C. V. | |
bibtex.entry.doi | 10.1080/1062936x.2013.871577 | en_US |
bibtex.entry.journal | SAR QSAR Environ. Res. | en_US |
bibtex.entry.month | Feb | |
bibtex.entry.number | 2 | en_US |
bibtex.entry.pages | 147–160 | en_US |
bibtex.entry.title | Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics | en_US |
bibtex.entry.volume | 25 | en_US |
bibtex.entry.year | 2014 | |
qdb.model.type | Regression model (regression) | en_US |
qdb.model.qmrf | Tab3_New=Q15-35-0009 |
Name | Description | Format | Size | View |
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2014SQER147.qdb.zip | QSAR for chronic fish toxicity | application/zip | 7.144Kb | View/ |
Q15-35-0009.pdf | QMRF | 35.23Kb | View/ |