Abstract
This study seeks to develop and test the recall of two search hedges for One Health articles. CAB s was searched, and the first 100 relevance-ranked results were downloaded. The most frequent co-occurrences of CAB descriptors were used to develop a hedge. A second hedge was developed using the descriptors and related natural language keywords. The natural language hedge had better recall (100% and 95%, respectively) than the co-occurrence hedge (24% and 86%, respectively). When searching a broad-based topic area like One Health, there is a need for expansive language to incorporate multiple expressions of a concept.
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