The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Historical Excursus on the Statistical Validation Parameters for QSAR Models: A Clarification Concerning Metrics and Terminology
Abstract
In the last years, external validation of QSAR models was the subject of intensive debate in the scientific literature. Different groups have proposed different metrics to find "the best" parameter to characterize the external predictivity of a QSAR model. This editorial summarizes the history of parameter development for the external QSAR model validation and suggests, once again, the concurrent use of several different metrics to assess the real predictive capability of QSAR models.
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Cites
Chai, T., & Draxler, R. R. (2014) · Geoscientific Model Development · doi:10.5194/gmd-7-1247-2014 · Cited by 7,178
Golbraikh, A., & Tropsha, A. (2002) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(01)00123-1 · Cited by 3,735
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“Instead, our focus is on the practical issues related to the applicability domain (168) and external predictivity validation (169).”
Background
Metadata
- Authors
- Gramatica, P., & Sangion, A.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-06-03
- Volume
- 56
- Issue
- 6
- Pages
- 1127-1131
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2398789413
- Cited by
- 420
- References
- 2
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Historical Excursus on the Statistical Validation Parameters for QSAR Models: A Clarification Concerning Metrics and Terminology. https://app.cochat.ai/papers/10.1021/acs.jcim.6b00088
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- Gramatica, P., & Sangion, A. (2016). A Historical Excursus on the Statistical Validation Parameters for QSAR Models: A Clarification Concerning Metrics and Terminology. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.6b00088
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