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Register a new userMeasuring Metrics - A forty year longitudinal cross-validation of citations, downloads, and peer review in Astrophysics
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Citation measures, and newer altmetric measures such as downloads are now commonly used to inform personnel decisions. How well do or can these measures measure or predict the past, current of future scholarly performance of an individual? Using data from the Smithsonian/NASA Astrophysics Data System we analyze the publication, citation, download, and distinction histories of a cohort of 922 individuals who received a U.S. PhD in astronomy in the period 1972-1976. By examining the same and different measures at the same and different times for the same individuals we are able to show the capabilities and limitations of each measure. Because the distributions are lognormal measurement uncertainties are multiplicative; we show that in order to state with 95% confidence that one persons citations and/or downloads are significantly higher than another persons, the log difference in the ratio of counts must be at least 0.3 dex, which corresponds to a multiplicative factor of two.
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I try to describe the stepwise progress in proving that massive black holes do exist in the Universe. As compared to forty years ago, measurements have pushed the size of the 4 million solar mass concentration in the Galactic Center downward by almost 10^6, and its density up by 10^18. Looking ahead toward the future, the question is probably no longer whether SgrA* must be a MBH, but rather whether GR is correct on the scales of the event horizon, whether space-time is described by the Kerr metric and whether the no hair theorem holds. Further improvements of the VLT interferometer GRAVITY (to GRAVITY+) and the next generation 25-40m telescopes (the ESO-ELT, the TMT and the GMT) promise further progress. A test of the no hair theorem in the Galactic Center might come from combining the stellar dynamics with EHT measurements of the photon ring of SgrA*.
We discuss microscopic mechanisms of complex network growth, with the special emphasis of how these mechanisms can be evaluated from the measurements on real networks. As an example we consider the network of citations to scientific papers. Contrary to common belief that its growth is determined by the linear preferential attachment, our microscopic measurements show that it is driven by the nonlinear autocatalytic growth. This invalidates the scale-free hypothesis for the citation network. The nonlinearity is responsible for a dramatic dynamical phase transition: while the citation lifetime of majority of papers is 6-10 years, the highly-cited papers have practically infinite lifetime.
Publication statistics are ubiquitous in the ratings of scientific achievement, with citation counts and paper tallies factoring into an individuals consideration for postdoctoral positions, junior faculty, tenure, and even visa status for international scientists. Citation statistics are designed to quantify individual career achievement, both at the level of a single publication, and over an individuals entire career. While some academic careers are defined by a few significant papers (possibly out of many), other academic careers are defined by the cumulative contribution made by the authors publications to the body of science. Several metrics have been formulated to quantify an individuals publication career, yet none of these metrics account for the dependence of citation counts and journal size on time. In this paper, we normalize publication metrics across both time and discipline in order to achieve a universal framework for analyzing and comparing scientific achievement. We study the publication careers of individual authors over the 50-year period 1958-2008 within six high-impact journals: CELL, the New England Journal of Medicine (NEJM), Nature, the Proceedings of the National Academy of Science (PNAS), Physical Review Letters (PRL), and Science. In comparing the achievement of authors within each journal, we uncover quantifiable statistical regularity in the probability density function (pdf) of scientific achievement across both time and discipline. The universal distribution of career success within these arenas for publication raises the possibility that a fundamental driving force underlying scientific achievement is the competitive nature of scientific advancement.
It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.
Bibliometric indicators, citation counts and/or download counts are increasingly being used to inform personnel decisions such as hiring or promotions. These statistics are very often misused. Here we provide a guide to the factors which should be considered when using these so-called quantitative measures to evaluate people. Rules of thumb are given for when begin to use bibliometric measures when comparing otherwise similar candidates.
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