Condensing the work of any academic scientist into a one-dimensional measure
of scientific quality is a difficult problem. Here, we employ Bayesian
statistics to analyze several different measures of quality. Specifically, we
determine each measure's ability to discriminate between scientific authors.
Using scaling arguments, we demonstrate that the best of these measures require
approximately 50 papers to draw conclusions regarding long term scientific
performance with usefully small statistical uncertainties. Further, the
approach described here permits the value-free (i.e., statistical) comparison
of scientists working in distinct areas of science.Comment: 11 pages, 8 figures, 4 table