OBJECTIVE:Impact Factors (IF) are widely used surrogates to evaluate single articles, in spite of
known shortcomings imposed by cite distribution skewness. We quantify this asymmetry and
propose a simple computer-based procedure for evaluating individual articles.METHOD:(a) Analysis of symmetry. Journals clustered around nine Impact
Factor points were selected from the medical “Subject Categories” in Journal
Citation Reports 2010. Citable items published in 2008 were retrieved and ranked by
granted citations over the Jan/2008 - Jun/2011 period. Frequency distribution of cites,
normalized cumulative cites and absolute cites/decile were determined for each journal
cluster. (b) Positive Predictive Value. Three arbitrarily
established evaluation classes were generated: LOW (1.3≤IF<2.6); MID:
(2.6≤IF<3.9); HIGH: (IF≥3.9). Positive Predictive Value
for journal clusters within each class range was estimated. (c) Continuously
Variable Rating. An alternative evaluation procedure is proposed to allow
the rating of individually published articles in comparison to all articles published in
the same journal within the same year of publication. The general guiding lines for the
construction of a totally dedicated software program are delineated.RESULTS AND CONCLUSIONS:Skewness followed the Pareto Distribution for (1