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Assessing non-standard article impact using F1000 labels

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Abstract

Faculty of 1000 (F1000) is a post-publishing peer review web site where experts evaluate and rate biomedical publications. F1000 reviewers also assign labels to each paper from a standard list or article types. This research examines the relationship between article types, citation counts and F1000 article factors (FFa). For this purpose, a random sample of F1000 medical articles from the years 2007 and 2008 were studied. In seven out of the nine cases, there were no significant differences between the article types in terms of citation counts and FFa scores. Nevertheless, citation counts and FFa scores were significantly different for two article types: “New finding” and “Changes clinical practice”: FFa scores value the appropriateness of medical research for clinical practice and “New finding” articles are more highly cited. It seems that highlighting key features of medical articles alongside ratings by Faculty members of F1000 could help to reveal the hidden value of some medical papers.

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Notes

  1. The CPP/FCSm is an indicator which developed by Centre for Science and Technology Studies (CWTS) with the aim of normalization of citation among different fields. It has been renamed as crown indicator (See http://arxiv.org/pdf/1003.2167.pdf).

References

  • Aksnes, D. W., & Taxt, R. E. (2004). Peer reviews and bibliometric indicators: A comparative study at a Norwegian university. Research Evaluation, 13(1), 33–41.

    Article  Google Scholar 

  • Allen, L., Jones, C., Dolby, K., Lynn, D., & Walport, M. (2009). Looking for landmarks: the role of expert review and bibliometric analysis in evaluating scientific publication outputs. PLoS ONE, 4(6), e5910.

    Article  Google Scholar 

  • Archambault, E., Campbell, D., Gingras, Y., & Lariviere, V. (2009). Comparing bibliometric statistics obtained from the Web of Science and Scopus. Journal of the American Society for Information Science and Technology, 60(7), 1320–1326.

    Article  Google Scholar 

  • Banzi, R., Moja, L., Pistotti, V., Facchini, A., & Liberati, A. (2011). Conceptual frameworks and empirical approaches used to assess the impact of health research: An overview of reviews. Health research policy and systems/BioMed Central, 9, 26. doi:10.1186/1478-4505-9-26.

    Article  Google Scholar 

  • Bornmann, L., & Daniel, H.-D. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64(1), 45–80.

    Article  Google Scholar 

  • Bornmann, L., & Leydesdorff, L. (2012). The validation of (advanced) bibliometric indicators through peer assessments: A comparative study using data from InCites and F1000. Digital Libraries; Applications. http://arxiv.org/abs/1211.1154.

  • Camacho-Miñano, M–. M., & Núñez-Nickel, Manuel. (2009). The multilayered nature of reference selection. Journal of the American Society for Information Science and Technology, 60(4), 754–777. doi:10.1002/asi.21018.

    Article  Google Scholar 

  • Chalmers, I., & Glasziou, P. (2009). Avoidable waste in the production and reporting of research evidence. Lancet, 374(9683), 86–89. doi:10.1016/S0140-6736(09)60329-9.

    Article  Google Scholar 

  • Cole, S., Cole, J. R., & Simon, G. A. (1981). Chance and consensus in peer review. Science, 214(4523), 881–886.

    Article  Google Scholar 

  • Cronin, B. (1984). The citation process. The role and significance of citations in scientific communication. London: Taylor Graham.

    Google Scholar 

  • F1000. (2012a). About F1000. http://f1000.com/prime/about/whatis.

  • F1000. (2012b). F1000 Faculty. http://f1000.com/prime/thefaculty.

  • Falagas, M. E., Kouranos, V. D., Arencibia-Jorge, R., & Karageorgopoulos, D. E. (2008). Comparison of SCImago journal rank indicator with journal impact factor. FASEB journal: official publication of the Federation of American Societies for Experimental Biology, 22(8), 2623–2628. doi:10.1096/fj.08-107938.

    Article  Google Scholar 

  • Field, A. (2009). Discovering statistics using SPSS. Thousand Oaks: SAGE.

    Google Scholar 

  • Fienberg, S. E., & Martin, M. E. (1985). Sharing research data. Washington: Natl Academy.

    Google Scholar 

  • Franceschet, M., & Costantini, A. (2011). The first Italian research assessment exercise: A bibliometric perspective. Journal of Informetrics, 5(2), 275–291.

    Article  Google Scholar 

  • Hanney, S., Frame, I., Grant, J., Buxton, M., Young, T., & Lewison, G. (2005). Using categorisations of citations when assessing the outcomes from health research. Scientometrics, 65(3), 357–379. doi:10.1007/s11192-005-0279-y.

    Article  Google Scholar 

  • Harnad, S. (1985). Rational disagreement in peer review. Science, Technology and Human Values, 10(3), 55–62.

    Article  MathSciNet  Google Scholar 

  • Huggett, S. (2012). F1000 Journal Rankings: An alternative way to evaluate the scientific impact of scholarly communications. Research Trends, 26, 7–11.

    Google Scholar 

  • Jones, T. H., Donovan, C., & Hanney, S. (2012). Tracing the wider impacts of biomedical research: A literature search to develop a novel citation categorisation technique. Scientometrics, 93(1), 125–134.

    Article  Google Scholar 

  • Koenig, M. E. D. (1982). Determinants of expert judgement of research performance. Scientometrics, 4(5), 361–378. doi:10.1007/BF02135122.

    Article  Google Scholar 

  • Kostoff, R. N. (1998). The use and misuse of citation analysis in research evaluation. Scientometrics, 43(1), 27–43. doi:10.1007/BF02458392.

    Article  Google Scholar 

  • Kostoff, R. N. (2007). The difference between highly and poorly cited medical articles in the journal Lancet. Scientometrics, 72(3), 513–520. doi:10.1007/s11192-007-1573-7.

    Article  Google Scholar 

  • Kousha, K., & Thelwall, M. (2008). Assessing the impact of disciplinary research on teaching: An automatic analysis of online syllabuses. Journal of the American Society for Information Science and Technology, 59(13), 2060–2069.

    Article  Google Scholar 

  • Kousha, K., Thelwall, M., & Rezaie, S. (2011). Assessing the citation impact of books: The role of Google Books, Google Scholar, and Scopus. Journal of the American Society for Information Science and Technology, 62(11), 2147–2164. doi:10.1002/asi.21608.

    Article  Google Scholar 

  • Kuruvilla, S., Mays, N., Pleasant, A., & Walt, G. (2006). Describing the impact of health research: A Research Impact Framework. BMC Health Services Research, 6(1), 134.

    Article  Google Scholar 

  • Lewison, G. (2005). Citations to papers from other documents. Handbook of Quantitative Science and Technology. http://www.springerlink.com/index/T2H0245570526217.pdf.

  • Lewison, T., & Sullivan, R. (2008). How do the media report cancer research? A study of the UK’s BBC website. British Journal of Cancer, 99(4), 569–576. doi:10.1038/sj.bjc.6604531.

    Article  Google Scholar 

  • Lewison, G., & Sullivan, R. (2008). The impact of cancer research: how publications influence UK cancer clinical guidelines. British Journal of Cancer, 98(12), 1944–1950. doi:10.1038/sj.bjc.6604405.

    Article  Google Scholar 

  • Li, & Thelwall, M. (2012). F1000, Mendeley and traditional bibliometric indicators. 17th International Conference on Science and Technology Indicators (Vol. 3, pp. 1–11).

  • MacRoberts, M. H., & MacRoberts, B. R. (1996). Problems of citation analysis. Scientometrics, 36(3), 435–444.

    Article  Google Scholar 

  • MacRoberts, M. H., & MacRoberts, B. R. (2010). Problems of citation analysis: A study of uncited and seldom-cited influences. Journal of the American Society for Information Science and Technology, 61(1), 1–12.

    Article  Google Scholar 

  • Mahdi, S., D’Este, P., & Neely, A. D. (2008). Citation counts: Are they good predictors of RAE scores?: A bibliometric analysis of RAE 2001. London: AIM Research.

    Google Scholar 

  • Maier, G. (2006). Impact factors and peer judgment: The case of regional science journals. Scientometrics, 69(3), 651–667.

    Article  Google Scholar 

  • Moed, H. F. (2005). Citation analysis in research evaluation (Vol. 9). Norwell: Kluwer Academic.

  • Nederhof, A. J., & Van Raan, A. F. J. (1993). A bibliometric analysis of six economics research groups: A comparison with peer review. Research Policy, 22(4), 353–368.

    Article  Google Scholar 

  • Niederkrotenthaler, T., Dorner, T. E., & Maier, M. (2011). Development of a practical tool to measure the impact of publications on the society based on focus group discussions with scientists. BMC Public Health, 11, 588. doi:10.1186/1471-2458-11-588.

    Article  Google Scholar 

  • Norris, M., & Oppenheim, C. (2003). Citation counts and the Research Assessment Exercise V: Archaeology and the 2001 RAE. Journal of Documentation, 59(6), 709–730.

    Article  Google Scholar 

  • Oppenheim, C. (1995). The correlation between citation counts and the 1992 Research Assessment Exercise Ratings for British library and information science university departments. Journal of Documentation, 51(1), 18–27.

    Article  MathSciNet  Google Scholar 

  • Oppenheim, C., & Summers, M. A. C. (2008). Citation counts and the Research Assessment Exercise, part VI: Unit of assessment 67 (music). Information Research, 13(2), 3.

    Google Scholar 

  • Opthof, T., & Leydesdorff, L. (2011). A comment to the paper by Waltman et al., Scientometrics, 87, 467–481, 2011. Scientometrics, 88(3), 1011–1016.

    Article  Google Scholar 

  • Piwowar, H. A., Day, R. S., & Fridsma, D. B. (2007). Sharing detailed research data is associated with increased citation rate. PLoS ONE, 2(3), e308. doi:10.1371/journal.pone.0000308.

    Article  Google Scholar 

  • Price, & Simon, (2009). Patient education and the impact of new medical research. Journal of Health Economics, 28(6), 1166–1174. doi:10.1016/j.jhealeco.2009.08.005.

    Article  Google Scholar 

  • Priem, & Hemminger, B. M. H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(7), http://frodo.lib.uic.edu/ojsjournals/index.php/fm/. Retrieved from http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2874.

  • Priem, Taraborelli, D., Groth, P., & Neylon, C. (2011). Altmetrics: A manifesto. http://altmetrics.org/manifesto.

  • Reale, E., Barbara, A., & Costantini, A. (2007). Peer review for the evaluation of academic research: lessons from the Italian experience. Research Evaluation, 16(3), 216–228.

    Article  Google Scholar 

  • Sarli, C. C., Dubinsky, E. K., & Holmes, K. L. (2010). Beyond citation analysis: A model for assessment of research impact. Journal of the Medical Library Association: JMLA, 98(1), 17–23.

    Article  Google Scholar 

  • Sarli, C. C., & Holmes, K. L. (2012). The becker medical library model for assessment of research impact. St Louis: Bernard Becker Medical Library, Washington University School of Medicine.

    Google Scholar 

  • Seglen, P. O. (1997). Citations and journal impact factors: questionable indicators of research quality. Allergy, 52(11), 1050–1056.

    Article  Google Scholar 

  • Seng, L. B., & Willett, P. (1995). The citedness of publications by United Kingdom library schools. Journal of Information Science, 21(1), 68–71.

    Article  Google Scholar 

  • Small, H. (2004). On the shoulders of Robert Merton: Towards a normative theory of citation. Scientometrics, 60(1), 71–79. http://www.springerlink.com/index/X6VTVM1209131570.pdf.

    Google Scholar 

  • Smith, A. T., & Eysenck, M. (2002). The correlation between RAE ratings and citation counts in psychology. London.

  • Stern, R. E. (1990). Uncitedness in the biomedical literature. Journal of the American society for information science, 41(3), 193–196.

    Article  Google Scholar 

  • Tomlinson, S. (2000). The research assessment exercise and medical research. British Medical Journal, 320(7235), 636–639.

    Article  Google Scholar 

  • Van Raan, A. F. J. (2006). Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups. Scientometrics, 67(3), 491–502.

    Google Scholar 

  • Vaughan, L., & Shaw, D. (2005). Web citation data for impact assessment: A comparison of four science disciplines. Journal of the American Society for Information Science and Technology, 56(10), 1075–1087.

    Article  Google Scholar 

  • Waltman, L., van Eck, N. J., van Leeuwen, T. N., Visser, M. S., & van Raan, A. F. J. (2011). On the correlation between bibliometric indicators and peer review: Reply to Opthof and Leydesdorff. Scientometrics, 3, 1017–1022.

    Article  Google Scholar 

  • Wardle, D. A. (2010). Do’Faculty of 1000′(F1000) ratings of ecological publications serve as reasonable predictors of their future impact? Ideas in Ecology and Evolution, 3, 11–15.

    Google Scholar 

  • Weiss, A. P. (2007). Measuring the impact of medical research: moving from outputs to outcomes. American Journal of Psychiatry, 164(2), 206.

    Article  Google Scholar 

  • Wets, K., Weedon, D., & Velterop, J. (2003). Post-publication filtering and evaluation: Faculty of 1000. Learned Publishing, 16(4), 249–258. doi:10.1087/095315103322421982.

    Article  Google Scholar 

  • Zaman, M. uz, & Britain, G. (2004). Review of the academic evidence on the relationship between teaching and research in higher education. https://www.education.gov.uk/publications/eOrderingDownload/RR506.pdf.

  • Zuccala, A. (2010). The mathematical review system: does reviewer status play a role in the citation process? Scientometrics, 84(1), 221–235.

    Article  Google Scholar 

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Correspondence to Ehsan Mohammadi.

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See Table 4.

Table 4 Faculty members of F1000 in different disciplines of medical sciences

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Mohammadi, E., Thelwall, M. Assessing non-standard article impact using F1000 labels. Scientometrics 97, 383–395 (2013). https://doi.org/10.1007/s11192-013-0993-9

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