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Such meta-research has analyzed and recently published, ultimately identifing the top 2% of the world's most influential scientists, in a unified way across each and every scientific sub-discipline. [9] [10] In general, the parameters that are taken into account and eventually determine the new composite-index (c-score) are the following ones:
The h-index is an author-level metric that measures both the productivity and citation impact of the publications, initially used for an individual scientist or scholar. The h-index correlates with success indicators such as winning the Nobel Prize, being accepted for research fellowships and holding positions at top universities. [1]
Research has indicated that bibliometrics figures, particularly the impact factor, decrease the quality of peer review an article receives, [80] cause a reluctance to share data, [21] decrease the quality of articles, [81] and a reduce the scope in of publishable research. "For many researchers the only research questions and projects that ...
In any given year, the CiteScore of a journal is the number of citations, received in that year and in previous three years, for documents published in the journal during the total period (four years), divided by the total number of published documents (articles, reviews, conference papers, book chapters, and data papers) in the journal during the same four-year period: [3]
Author-level metrics are citation metrics that measure the bibliometric impact of individual authors, researchers, academics, and scholars. Many metrics have been developed that take into account varying numbers of factors (from only considering the total number of citations, to looking at their distribution across papers or journals using statistical or graph-theoretic principles).
where CF—the cumulative frequency—is the count of all scores less than or equal to the score of interest, F is the frequency for the score of interest, and N is the number of scores in the distribution. Alternatively, if CF ' is the count of all scores less than the score of interest, then
Composite measure in statistics and research design refer to composite measures of variables, i.e. measurements based on multiple data items. [1] An example of a composite measure is an IQ test, which gives a single score based on a series of responses to various questions. Three common composite measures include:
Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.