Discovering discoveries: Identifying biomedical discoveries using citation contexts

被引:45
|
作者
Small, Henry [1 ]
Tseng, Hung [2 ]
Patek, Mike [3 ]
机构
[1] SciTech Strategies Inc, 105 Rolling Rd, Bala Cynwyd, PA 19004 USA
[2] NIAMSD, NIH, 6701 Democracy Blvd, Bethesda, MD 20892 USA
[3] SciTech Strategies Inc, 58 Russell St, Keene, NH 03431 USA
关键词
Discovery; Biomedicine; Citation contexts; Citances; Machine learning; Pubmed central;
D O I
10.1016/j.joi.2016.11.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A procedure for identifying discoveries in the biomedical sciences is described that makes use of citation context information, or more precisely citing sentences, drawn from the PubMed Central database. The procedure focuses on use of specific terms in the citing sentences and the joint appearance of cited references. After a manual screening process to remove non -discoveries, a list of over 100 discoveries and their associated articles is compiled and characterized by subject matter and by type of discovery. The phenomenon of multiple discovery is shown to play an important role. The onset and timing of recognition of the articles are studied by comparing the number of citing sentences with and without discovery terms, and show both early onset and delays in recognition. A comparative analysis of the vocabularies of the discovery and non -discovery sentences reveals the types of words and concepts that scientists associate with discoveries. A machine learning application is used to efficiently extend the list. Implications of the findings for understanding the nature and justification of scientific discoveries are discussed. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:46 / 62
页数:17
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