2013/03/15 by Ludo Waltman, Waltman, Ludo, Rodrigo Costas +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · Medicine · Psychology · #Biomedical Text Mining and Ontologies #Citation #Computer science #Data science #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Information retrieval #Library science #MEDLINE #Medicine #Meta-analysis and systematic reviews #Perspective (graphical) #Political science #Psychology #cs.DL #scientometrics and bibliometrics research
paper · pdf · doi:10.48550/arxiv.1303.3875
arxiv created 2013/03/15 · openalex publication_date 2013/03/15 · arxiv updated 2013/03/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
F1000 is a post-publication peer review service for biological and medical\nresearch. F1000 aims to recommend important publications in the biomedical\nliterature, and from this perspective F1000 could be an interesting tool for\nresearch evaluation. By linking the complete database of F1000 recommendations\nto the Web of Science bibliographic database, we are able to make a\ncomprehensive comparison between F1000 recommendations and citations. We find\nthat about 2% of the publications in the biomedical literature receive at least\none F1000 recommendation. Recommended publications on average receive 1.30\nrecommendations, and over 90% of the recommendations are given within half a\nyear after a publication has appeared. There turns out to be a clear\ncorrelation between F1000 recommendations and citations. However, the\ncorrelation is relatively weak, at least weaker than the correlation between\njournal impact and citations. More research is needed to identify the main\nreasons for differences between recommendations and citations in assessing the\nimpact of publications.\n