Thus, we limited the grant-to-article linkage set to those grants that have produced a minimum of four articles.
We created a metric based on grant acknowledgements from MEDLINE, using a grant-to-article linkage dataset from a previous study [46].
The two MeSHOP gene article linkage collections are both used in the subsequently described validation.
Precision-recall curves were calculated for each cluster solution using the set of grant-to-article linkages mentioned above, and are shown in Figure 3.
We calculate two different concentration measures based on grant-to-article linkages: a standard concentration (or Herfindahl) index and precision-recall.
We chose to assess and compare cluster solutions using two different types of validation measures: (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) concentration measures based on grant-to-article linkages indexed in MEDLINE.
We measure cluster quality using a textual coherence measure based on the Jensen-Shannon divergence [27], and using concentration measures based on the grant-to-article linkages indexed in MEDLINE.
Cluster results from the nine similarity approaches were compared using (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) two concentration measures based on grant-to-article linkages indexed in MEDLINE.
The premise for using grant-to-article linkages as a metric for measuring the accuracy of a cluster solution is the assumption that the articles acknowledging a single grant should be highly related, and should be concentrated in a cluster solution of the document space.
Two sources for gene-article linkages from Entrez Gene were evaluated: Gene Reference Into Function (GeneRIF) and gene2pubmed.
In this article the linkage between the science of toxicology and the needs of governmental regulatory agencies in the United States is explored through an overview of environmental regulations enacted over the past century and a brief history of modern toxicology.
