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Reputation is an important social construct in science, which enables informed quality assessments of both publications and careers of scientists in the absence of complete systemic information. However, the relation between reputation and career growth of an individual remains poorly understood, despite recent proliferation of quantitative research evaluation methods. Here we develop an original framework for measuring how a publications citation rate $Delta c$ depends on the reputation of its central author $i$, in addition to its net citation count $c$. To estimate the strength of the reputation effect, we perform a longitudinal analysis on the careers of 450 highly-cited scientists, using the total citations $C_{i}$ of each scientist as his/her reputation measure. We find a citation crossover $c_{times}$ which distinguishes the strength of the reputation effect. For publications with $c < c_{times}$, the authors reputation is found to dominate the annual citation rate. Hence, a new publication may gain a significant early advantage corresponding to roughly a 66% increase in the citation rate for each tenfold increase in $C_{i}$. However, the reputation effect becomes negligible for highly cited publications meaning that for $cgeq c_{times}$ the citation rate measures scientific impact more transparently. In addition we have developed a stochastic reputation model, which is found to reproduce numerous statistical observations for real careers, thus providing insight into the microscopic mechanisms underlying cumulative advantage in science.
Analyzing a large data set of publications drawn from the most competitive journals in the natural and social sciences we show that research careers exhibit the broad distributions of individual achievement characteristic of systems in which cumulati
We stress-test the career predictability model proposed by Acuna et al. [Nature 489, 201-202 2012] by applying their model to a longitudinal career data set of 100 Assistant professors in physics, two from each of the top 50 physics departments in th
We present a simple generalization of Hirschs h-index, Z = sqrt{h^{2}+C}/sqrt{5}, where C is the total number of citations. Z is aimed at correcting the potentially excessive penalty made by h on a scientists highly cited papers, because for the majo
Correctly assessing a scientists past research impact and potential for future impact is key in recruitment decisions and other evaluation processes. While a candidates future impact is the main concern for these decisions, most measures only quantif
Problems for evaluation and impact of published scientific works and their authors are discussed. The role of citations in this process is pointed out. Different bibliometric indicators are reviewed in this connection and ways for generation of new b