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  • × author_ss:"Schreiber, M."
  1. Schreiber, M.: Uncertainties and ambiguities in percentiles and how to avoid them (2013) 0.05
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    Date
    22. 3.2013 19:52:05
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.640-643
  2. Schreiber, M.: Revisiting the g-index : the average number of citations in the g-core (2009) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.1, S.169-174
  3. Schreiber, M.: Inconsistencies in the highly cited publications indicator (2013) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.6, S.1298-1302
  4. Schreiber, M.: Do we need the g-index? (2013) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2396-2399
  5. Schreiber, M.: ¬An empirical investigation of the g-index for 26 physicists in comparison with the h-index, the A-index, and the R-index (2008) 0.01
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    Abstract
    J.E. Hirsch (2005) introduced the h-index to quantify an individual's scientific research output by the largest number h of a scientist's papers that received at least h citations. To take into account the highly skewed frequency distribution of citations, L. Egghe (2006a) proposed the g-index as an improvement of the h-index. I have worked out 26 practical cases of physicists from the Institute of Physics at Chemnitz University of Technology, and compare the h and g values in this study. It is demonstrated that the g-index discriminates better between different citation patterns. This also can be achieved by evaluating B.H. Jin's (2006) A-index, which reflects the average number of citations in the h-core, and interpreting it in conjunction with the h-index. h and A can be combined into the R-index to measure the h-core's citation intensity. I also have determined the A and R values for the 26 datasets. For a better comparison, I utilize interpolated indices. The correlations between the various indices as well as with the total number of papers and the highest citation counts are discussed. The largest Pearson correlation coefficient is found between g and R. Although the correlation between g and h is relatively strong, the arrangement of the datasets is significantly different depending on whether they are put into order according to the values of either h or g.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.9, S.1513-1522
  6. Schreiber, M.: ¬A case study of the modified Hirsch index hm accounting for multiple coauthors (2009) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1274-1282
  7. Schreiber, M.: Empirical evidence for the relevance of fractional scoring in the calculation of percentile rank scores (2013) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.4, S.861-867
  8. Schreiber, M.: ¬A variant of the h-index to measure recent performance (2015) 0.01
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2373-2380
  9. Schreiber, M.: Fractionalized counting of publications for the g-Index (2009) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.2145-2150
  10. Waltman, L.; Schreiber, M.: On the calculation of percentile-based bibliometric indicators (2013) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.372-379
  11. Schreiber, M.: Inconsistencies of recently proposed citation impact indicators and how to avoid them (2012) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.10, S.2062-2073