Publication metrics and success on the academic job market David van Dijk, Ohad Manor, Lucas B. Carey  Current Biology  Volume 24, Issue 11, Pages R516-R517 (June 2014) DOI: 10.1016/j.cub.2014.04.039 Copyright © 2014 Elsevier Ltd Terms and Conditions

Figure 1 Publication features, prior to becoming a PI or leaving academia, accurately separate future PIs from non-PIs. (A) In our data set of 25,604 authors, 1583 (6.2%) become a PI (A, left). (A, right) Histogram of the distribution of time to PI for all authors that become PIs. (B) Shown are publication features that separate PIs from non-PIs. The blue bar shows the total fraction (6.2%) of authors that become PIs. Green, red, cyan, magenta, orange and yellow bars show the fraction of authors in the top 10% for a given grouping that becomes a PI. Error bars show the standard deviation for this calculated fraction following 100 bootstraps. For each author, only non-last author publications prior to becoming a PI are used for the calculation. (B, cyan bar) Authors are grouped according to the mean number of citations per IF (journal impact factor) for publications in which they are first author (left cyan bar) or middle author (right cyan bar). (B, magenta bar) Authors are grouped according to the mean number of citations for publications in which they are first author (left magenta bar) or middle author (right magenta bar). (B, orange bar) Authors are grouped according to their average number of co-authors, for papers in which they are either first (left yellow bar) or middle (right yellow bar) author. (B, yellow bar) Authors are grouped according to their h-index. (C) Principal component analysis is shown in which the first two principal components explain 92% of the variance. Future PIs are shown in blue circles, future non-PIs in green triangles. (D–G) Shown are the trajectories of various publication features in time, for authors that will eventually become PI and for authors that will eventually leave academia. Dotted lines are error-bars obtained by bootstrapping. Authors who will eventually become PI (red lines) show, on average (compared to authors who will eventually leave academia, blue lines), already in early career, an increased rate of publication (D, mean publication rate in time), and an increased journal impact factor (E, mean IF in time). Authors that have longer pre-PI careers show an increased number of citations per IF (F, mean number of citations per IF in time). Authors who will eventually become PI go to higher ranked universities (G, mean university rank in time). In addition, for authors that will become PI, university rank appears to increase within the first 5 years of their careers (G, arrow). Current Biology 2014 24, R516-R517DOI: (10.1016/j.cub.2014.04.039) Copyright © 2014 Elsevier Ltd Terms and Conditions