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When conducting exhaustive searches for systematic reviews, information professionals search multiple databases with overlapping content [1][2][3][4].They typically remove duplicate records to reduce the reviewers' workload associated with screening titles and abstracts; sometimes the reviewers remove the duplicates.Several articles have been published recently on de-duplication methods.In the authors' opinion, these methods are either very time consuming [5] or impractical, as they require uploading large files to an online platform [6,7].A recent overview article compared existing software programs but found that none was truly satisfactory [8].Unique identifiers for journal articles are digital object identifiers (DOIs) and PubMed IDs (PMIDs).However, these identifiers are not present in every database.When they are present, they often cannot be exported easily.Thus, they cannot be relied upon to identify duplicates.An alternative involves using pagination, because the often large page numbers in scientific journals, in combination with other fields, can serve as a type of unique identifier.However, this is complicated by variations in the way page numbers are stored.Most biomedical databases use a long format (e.g.,
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Stored only when both papers are in the corpus — 1,926 citations exist upstream.
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