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  • 标题:Search results outliers among MEDLINE platforms
  • 本地全文:下载
  • 作者:Christopher Sean Burns ; Robert M. Shapiro II ; Tyler Nix
  • 期刊名称:Journal of the Medical Library Association
  • 印刷版ISSN:1536-5050
  • 出版年度:2019
  • 卷号:107
  • 期号:3
  • 页码:364-373
  • DOI:10.5195/jmla.2019.622
  • 出版社:Medical Library Association
  • 摘要:Objective Hypothetically, content in MEDLINE records is consistent across multiple platforms. Though platforms have different interfaces and requirements for query syntax, results should be similar when the syntax is controlled for across the platforms. The authors investigated how search result counts varied when searching records among five MEDLINE platforms. Methods We created 29 sets of search queries targeting various metadata fields and operators. Within search sets, we adapted 5 distinct, compatible queries to search 5 MEDLINE platforms (PubMed, ProQuest, EBSCO host , Web of Science, and Ovid), totaling 145 final queries. The 5 queries were designed to be logically and semantically equivalent and were modified only to match platform syntax requirements. We analyzed the result counts and compared PubMed’s MEDLINE result counts to result counts from the other platforms. We identified outliers by measuring the result count deviations using modified z-scores centered around PubMed’s MEDLINE results. Results Web of Science and ProQuest searches were the most likely to deviate from the equivalent PubMed searches. EBSCO host and Ovid were less likely to deviate from PubMed searches. Ovid’s results were the most consistent with PubMed’s but appeared to apply an indexing algorithm that resulted in lower retrieval sets among equivalent searches in PubMed. Web of Science exhibited problems with exploding or not exploding Medical Subject Headings (MeSH) terms. Conclusion Platform enhancements among interfaces affect record retrieval and challenge the expectation that MEDLINE platforms should, by default, be treated as MEDLINE. Substantial inconsistencies in search result counts, as demonstrated here, should raise concerns about the impact of platform-specific influences on search results.
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