The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Quantifying the evolution of individual scientific impact
Open accessAbstract
Scientific impact—that is the Q: Are there quantifiable patterns behind a successful scientific career? Sinatra et al. analyzed the publications of 2887 physicists, as well as data on scientists publishing in a variety of fields. When productivity (which is usually greatest early in the scientist's professional life) is accounted for, the paper with the greatest impact occurs randomly in a scientist's career. However, the process of generating a high-impact paper is not an entirely random one. The authors developed a quantitative model of impact, based on an element of randomness, productivity, and a factor Q that is particular to each scientist and remains constant during the scientist's career. Science , this issue p. 596
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Cites
An Introduction to Statistical Modeling of Extreme Values
Coles, S. (2001) · Springer Series in Statistics · doi:10.1007/978-1-4471-3675-0 · Cited by 7,352
The Increasing Dominance of Teams in Production of Knowledge
Wuchty, S., Jones, B. F., & Uzzi, B. (2007) · Science · doi:10.1126/science.1136099 · Cited by 3,615
Bibliometrics: The Leiden Manifesto for Research Metrics
Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015) · Nature · doi:10.1038/520429a · Cited by 2,828
Universality of citation distributions: Toward an objective measure of scientific impact
Radicchi, F., Fortunato, S., & Castellano, C. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806977105 · Cited by 828
Citation Statistics from 110 Years of Physical Review
Redner, S. (2005) · Physics Today · doi:10.1063/1.1996475 · Cited by 426
Acuna, D. E., Allesina, S., & Kording, K. P. (2012) · Nature · doi:10.1038/489201a · Cited by 249
Persistence and uncertainty in the academic career
Petersen, A. M., Riccaboni, M., Stanley, H. E., & Pammolli, F. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121429109 · Cited by 188
Cited by
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497
Self-citationHistorical comparison of gender inequality in scientific careers across countries and disciplines
Huang, J., Gates, A. J., Sinatra, R., & Barabási, A.-L. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1914221117 · Cited by 954
Self-citationThe Matthew effect in science funding
Bol, T., de Vaan, M., & van de Rijt, A. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1719557115 · Cited by 638
The preeminence of ethnic diversity in scientific collaboration
AlShebli, B. K., Rahwan, T., & Woon, W. L. (2018) · Nature Communications · doi:10.1038/s41467-018-07634-8 · Cited by 490
Data-driven predictions in the science of science
Clauset, A., Larremore, D. B., & Sinatra, R. (2017) · Science · doi:10.1126/science.aal4217 · Cited by 265
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Metadata
- Authors
- Sinatra, R., Wang, D., Deville, P., Song, C., & Barabási, A.-L.
- Venue
- Science
- Published
- 2016-11-04
- Volume
- 354
- Issue
- 6312
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2547045893
- Cited by
- 619
- References
- 7
- FWCI
- 51.64
- Type
- journal article
- Language
- en
- Open access
- green
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