Predicting scientific success
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Success at publishing can help predict scientists' future success.
“can help predict their future success [2]”
From Ten simple rules for structuring papers (2017) · cites this paper as [2]
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Regularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957 · see citing works
An index to quantify an individual’s scientific research output
Hirsch, J. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507655102 · Cited by 11,669 · see citing works
Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias
Dwan, K., Altman, D. G., Arnaiz, J. A., Bloom, J., Chan, A.-W., Cronin, E., Decullier, E., Easterbrook, P. J., Von Elm, E., Gamble, C., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003081 · Cited by 1,546 · see citing works
Race, Ethnicity, and NIH Research Awards
Ginther, D. K., Schaffer, W. T., Schnell, J. D., Masimore, B., Liu, F., Laurel, H., & Kington, R. S. (2011) · Science · doi:10.1126/science.1196783 · Cited by 1,084 · see citing works
Does the h index have predictive power?
Hirsch, J. E. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707962104 · Cited by 980 · see citing works
Alonso, S., Cabrerizo, F. J., Herrera‐Viedma, E., & Herrera, F. (2009) · Journal of Informetrics · doi:10.1016/j.joi.2009.04.001 · Cited by 841 · see citing works
Measuring Nepotism through Shared Last Names: The Case of Italian Academia
Allesina, S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021160 · Cited by 88 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [3]Peterson I ScienceNews 2 12 2005 available at http://go.nature.com/iawd5o
Cited by
Sorted by citations
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 · see citing works
Quantifying Long-Term Scientific Impact
Wang, D., Song, C., & Barabási, A.-Ĺ. (2013) · Science · doi:10.1126/science.1237825 · Cited by 850 · see citing works
Quantifying the evolution of individual scientific impact
Sinatra, R., Wang, D., Deville, P., Song, C., & Barabási, A.-Ĺ. (2016) · Science · doi:10.1126/science.aaf5239 · Cited by 613 · see citing works
Yang, D.-Z., Kleissl, J., Gueymard, C., Pedro, H., & Coimbra, C. (2018) · Solar Energy · doi:10.1016/j.solener.2017.11.023 · Cited by 508 · see citing works
The Matthew effect in empirical data
Perc, M. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0378 · Cited by 556 · see citing works
The science of science: From the perspective of complex systems
Zeng, A., Shen, Z., Zhou, J., Wu, J., Fan, Y., Wang, Y., & Stanley, E. (2017) · Physics Reports · doi:10.1016/j.physrep.2017.10.001 · Cited by 406 · see citing works
Early coauthorship with top scientists predicts success in academic careers
Li, W., Aste, T., Caccioli, F., & Livan, G. (2019) · Nature Communications · doi:10.1038/s41467-019-13130-4 · Cited by 256 · see citing works
Publication metrics and success on the academic job market
van Dijk, D., Manor, O., & Carey, L. B. (2014) · Current Biology · doi:10.1016/j.cub.2014.04.039 · Cited by 238 · see citing works
Ranking in evolving complex networks
Liao, H., Mariani, M. S., Medo, M., Zhang, Y., & Zhou, M.-Y. (2017) · Physics Reports · doi:10.1016/j.physrep.2017.05.001 · Cited by 234 · see citing works
Ranking in evolving complex networks
Liao, H., Mariani, M. S., Medo, M., Zhang, Y., & Zhou, M. (2017) · reroDoc Digital Library · Cited by 221 · see citing works
The h-index is no longer an effective correlate of scientific reputation
Koltun, V., & Hafner, D. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253397 · Cited by 213 · see citing works
The advantage of short paper titles
Letchford, A., Moat, H. S., & Preis, T. (2015) · Royal Society Open Science · doi:10.1098/rsos.150266 · Cited by 184 · see citing works
Lowry, P. B., Moody, G. D., Gaskin, J. E., Galletta, D. F., Humpherys, S. L., Barlow, J. B., & Wilson, D. W. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.4.01 · Cited by 188 · see citing works
Predicting scientific success based on coauthorship networks
Sarigöl, E., Pfitzner, R., Scholtes, I., Garas, A., & Schweitzer, F. (2014) · EPJ Data Science · doi:10.1140/epjds/s13688-014-0009-x · Cited by 174 · see citing works
The Future of Women in Psychological Science
Gruber, J., Mendle, J., Lindquist, K. A., Schmader, T., Clark, L. A., Bliss‐Moreau, E., Akinola, M., Atlas, L. Y., Barch, D. M., Barrett, L. F., et al. (2020) · Perspectives on Psychological Science · doi:10.1177/1745691620952789 · Cited by 145 · see citing works
On the Predictability of Future Impact in Science
Penner, O., Pan, R. K., Petersen, A. M., Kaski, K., & Fortunato, S. (2013) · Scientific Reports · doi:10.1038/srep03052 · Cited by 140 · see citing works
Early-career setback and future career impact
Wang, Y., Jones, B. F., & Wang, D. (2019) · Nature Communications · doi:10.1038/s41467-019-12189-3 · Cited by 137 · see citing works
Predicting citation counts based on deep neural network learning techniques
Abrishami, A., & Aliakbary, S. (2019) · RePEc: Research Papers in Economics · Cited by 124 · see citing works
Predicting citation counts based on deep neural network learning techniques
Abrishami, A., & Aliakbary, S. (2019) · Journal of Informetrics · doi:10.1016/j.joi.2019.02.011 · Cited by 117 · see citing works
Solving the Productivity and Impact Puzzle: Do Men Outperform Women, or are Metrics Biased?
Cameron, E. Z., White, A. M., & Gray, M. E. (2016) · BioScience · doi:10.1093/biosci/biv173 · Cited by 111 · see citing works
Predicting the long-term citation impact of recent publications
Stegehuis, C., Litvak, N., & Waltman, L. (2015) · Journal of Informetrics · doi:10.1016/j.joi.2015.06.005 · Cited by 109 · see citing works
On the Predictability of Future Impact in Science
Penner, O., Pan, R. K., Petersen, A. M., Kaski, K. K., & Fortunato, S. (2013) · IMT Institutional Repository (IMT School for Advanced Studies Lucca) · Cited by 102 · see citing works
Predicting publication success for biologists
Laurance, W. F., Useche, D. C., Laurance, S. G., & Bradshaw, C. J. A. (2013) · BioScience · doi:10.1525/bio.2013.63.10.9 · Cited by 100 · see citing works
Standing on the shoulders of giants
Amjad, T., Ding, Y., Xu, J., Zhang, C., Daud, A. Y., Tang, J., & Song, M. (2017) · Journal of Informetrics · doi:10.1016/j.joi.2017.01.004 · Cited by 98 · see citing works
Methods to account for citation inflation in research evaluation
Petersen, A. M., Pan, R. K., Fabio Pammolli, A., & Fortunato, S. (2019) · Research Policy · doi:10.1016/j.respol.2019.04.009 · Cited by 91 · see citing works
Sociological Innovation through Subfield Integration
Leahey, E., & Moody, J. W. (2014) · Social Currents · doi:10.1177/2329496514540131 · Cited by 93 · see citing works
A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations
Dong, Y., Ma, H., Shen, Z., & Wang, K. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/3097983.3098016 · Cited by 89 · see citing works
The h-index Debate: An Introduction for Librarians
Barnes, C. (2017) · The Journal of Academic Librarianship · doi:10.1016/j.acalib.2017.08.013 · Cited by 87 · see citing works
Ten simple rules for structuring papers
Mensh, B., & Kording, K. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005619 · Cited by 85 · see citing works
“Indeed, success at publishing is used to evaluate scientists [1] and can help predict their future success [2].”
BackgroundSelf-citationCan Scientific Impact Be Predicted?
Dong, Y., Johnson, R. A., & Chawla, N. V. (2016) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2016.2521657 · Cited by 84 · see citing works
The h-Index: Understanding its predictors, significance, and criticism
Mondal, H., Deepak, K. K., Gupta, M., & Kumar, R. (2023) · Journal of Family Medicine and Primary Care · doi:10.4103/jfmpc.jfmpc_1613_23 · Cited by 79 · see citing works
On modeling and predicting individual paper citation count over time
Xiao, S., Yan, J., Li, C., Jin, B., Wang, X., Yang, X., Chu, S. M., & Zhu, H. (2016) · International Joint Conference on Artificial Intelligence · Cited by 75 · see citing works
Predicting the impact of scientific concepts using full-text features
McKeown, K., Daume, H., Chaturvedi, S., Paparrizos, J., Thadani, K., Barrio, P., Biran, O., Bothe, S., Collins, M., Fleischmann, K. R., et al. (2016) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23612 · Cited by 73 · see citing works
Krauß, A., Danús, L., & Sales‐Pardo, M. (2023) · Scientific Reports · doi:10.1038/s41598-023-46050-x · Cited by 75 · see citing works
Early indicators of scientific impact: Predicting citations with altmetrics
Akella, A. P., Alhoori, H., Kondamudi, P. R., Freeman, C., & Zhou, H. (2021) · Journal of Informetrics · doi:10.1016/j.joi.2020.101128 · Cited by 74 · see citing works
Growing complex network of citations of scientific papers: Modeling and measurements
Golosovsky, M., & Solomon, S. (2017) · Physical review. E · doi:10.1103/physreve.95.012324 · Cited by 70 · see citing works
Gender and the h index in psychology
Geraci, L. D., Balsis, S. M., & Busch, A. (2015) · Scientometrics · doi:10.1007/s11192-015-1757-5 · Cited by 67 · see citing works
Profit (p)-Index: The Degree to Which Authors Profit from Co-Authors
Aziz, N. A., & Rozing, M. P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059814 · Cited by 61 · see citing works
Hu, Y.-H., Tai, C.-T., Liu, K. E., & Cai, C.-F. (2020) · Journal of Informetrics · doi:10.1016/j.joi.2019.101004 · Cited by 62 · see citing works
Learning on knowledge graph dynamics provides an early warning of impactful research
Weis, J. W., & Jacobson, J. M. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00907-6 · Cited by 62 · see citing works
Network-Driven Reputation in Online Scientific Communities
Liao, H., Xiao, R., Cimini, G., & Medo, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112022 · Cited by 58 · see citing works
On the very idea of pursuitworthiness
Shaw, J. (2021) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2021.11.016 · Cited by 58 · see citing works
Early-career setback and future career impact
Wang, Y., Jones, B. F., & Wang, D. (2019) · RePEc: Research Papers in Economics · Cited by 58 · see citing works
A data analytic approach to quantifying scientific impact
Cao, X., Chen, Y., & Liu, K. J. R. (2016) · Journal of Informetrics · doi:10.1016/j.joi.2016.02.006 · Cited by 52 · see citing works
Qi, M., Zeng, A., Li, M., Fan, Y., & Di, Z. (2017) · Scientometrics · doi:10.1007/s11192-017-2328-8 · Cited by 54 · see citing works
Exploiting citation networks for large-scale author name disambiguation
Schulz, C., Mazloumian, A., Petersen, A. M., Penner, O., & Helbing, D. (2014) · EPJ Data Science · doi:10.1140/epjds/s13688-014-0011-3 · Cited by 71 · see citing works
Exploiting citation networks for large-scale author name disambiguation
Schulz, C., Mazloumian, A., Petersen, A. M., Penner, O., & Helbing, D. (2014) · IMT Institutional Repository (IMT School for Advanced Studies Lucca) · doi:10.3929/ethz-b-000091888 · Cited by 53 · see citing works
AlShebli, B., Makovi, K., & Rahwan, T. (2020) · Nature Communications · doi:10.1038/s41467-020-19723-8 · Cited by 52 · see citing works
RetractedKaltman, J. R., Evans, F. J., Danthi, N. S., Wu, C. O., DiMichele, D., & Lauer, M. S. (2014) · Circulation Research · doi:10.1161/circresaha.115.304766 · Cited by 51 · see citing works
The advantage of simple paper abstracts
Letchford, A., Preis, T., & Moat, H. S. (2015) · Journal of Informetrics · doi:10.1016/j.joi.2015.11.001 · Cited by 49 · see citing works
Structure-oriented prediction in complex networks
Ren, Z.-M., Zeng, A., & Zhang, Y. (2018) · Physics Reports · doi:10.1016/j.physrep.2018.05.002 · Cited by 47 · see citing works
Predicting the research performance of early career scientists
Lee, D. H. (2019) · Scientometrics · doi:10.1007/s11192-019-03232-7 · Cited by 49 · see citing works
Moreira, J. A. G., Zeng, X. H. T., & Amaral, L. A. N. (2015) · PLoS ONE · doi:10.1371/journal.pone.0143108 · Cited by 48 · see citing works
Carli, G., Tagliaventi, M. R., & Cutolo, D. (2018) · Studies in Higher Education · doi:10.1080/03075079.2018.1466873 · Cited by 47 · see citing works
Schreiber, M. (2015) · Journal of Informetrics · doi:10.1016/j.joi.2014.12.005 · Cited by 47 · see citing works
How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index
Schreiber, M. (2013) · RePEc: Research Papers in Economics · Cited by 45 · see citing works
Quantifying and predicting success in show business
Williams, O. E., Lacasa, L., & Latora, V. (2019) · Nature Communications · doi:10.1038/s41467-019-10213-0 · Cited by 45 · see citing works
The time dimension of science: Connecting the past to the future
Yin, Y., & Wang, D. (2017) · Journal of Informetrics · doi:10.1016/j.joi.2017.04.002 · Cited by 49 · see citing works
Predicting scientific impact based on h-index
Ayaz, S., Masood, N., & Islam, M. A. (2017) · Scientometrics · doi:10.1007/s11192-017-2618-1 · Cited by 42 · see citing works
How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index
Schreiber, M. (2013) · Journal of Informetrics · doi:10.1016/j.joi.2013.01.001 · Cited by 40 · see citing works
The classical origin of modern mathematics
Gargiulo, F., Caen, A., Lambiotte, R., & Carletti, T. (2016) · EPJ Data Science · doi:10.1140/epjds/s13688-016-0088-y · Cited by 40 · see citing works
Exploring the determinants of research performance for early-career researchers: a literature review
Lee, D. H. (2023) · Scientometrics · doi:10.1007/s11192-023-04868-2 · Cited by 40 · see citing works
Recent trends in the U.S. Behavioral and Social Sciences Research (BSSR) workforce
Hur, H., Andalib, M. A., Maurer, J. A., Hawley, J. D., & Ghaffarzadegan, N. (2017) · PLoS ONE · doi:10.1371/journal.pone.0170887 · Cited by 36 · see citing works
von Bartheld, C. S., Houmanfar, R. A., & Candido, A. (2015) · PeerJ · doi:10.7717/peerj.1262 · Cited by 35 · see citing works
Loss of sustainability in scientific work
Reisz, N., Servedio, V. D. P., Loreto, V., Schueller, W., Ferreira, M. R., & Stefan Thurner, A. (2022) · New Journal of Physics · doi:10.1088/1367-2630/ac6ca1 · Cited by 34 · see citing works
A review of scientific impact prediction: tasks, features and methods
Xia, W., Li, T., & Li, C. (2022) · Scientometrics · doi:10.1007/s11192-022-04547-8 · Cited by 35 · see citing works
Implicit Multi-Feature Learning for Dynamic Time Series Prediction of the Impact of Institutions
Bai, X., Zhang, F., Hou, J., Xia, F., Tolba, A. K. R., & Elashkar, E. E. (2017) · IEEE Access · doi:10.1109/access.2017.2739179 · Cited by 32 · see citing works
Xu, J., Li, M., Jiang, J., Ge, B., & Cai, M. (2019) · IEEE Access · doi:10.1109/access.2019.2927011 · Cited by 32 · see citing works
The Perks and Perils of Interdisciplinary Research
Leahey, E. (2018) · European Review · doi:10.1017/s1062798718000261 · Cited by 31 · see citing works
Prediction methods and applications in the science of science: A survey
Hou, J., Pan, H., Guo, T., Lee, I., Kong, X., & Xia, F. (2019) · Computer Science Review · doi:10.1016/j.cosrev.2019.100197 · Cited by 31 · see citing works
Bibliometrics for Internet media: Applying the h‐index to Y ou T ube
Hovden, R. (2013) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22936 · Cited by 29 · see citing works
The time dimension of science: Connecting the past to the future
Yin, Y., & Wang, D. (2017) · RePEc: Research Papers in Economics · Cited by 30 · see citing works
Science behind AI: the evolution of trend, mobility, and collaboration
Yuan, S., Shao, Z., Wei, X., Tang, J., Hall, W., Wang, Y., Wang, Y., & Wang, Y. (2020) · Scientometrics · doi:10.1007/s11192-020-03423-7 · Cited by 29 · see citing works
Commentary: The case for caution in predicting scientists’ future impact
Penner, O., Petersen, A. M., Pan, R. K., & Fortunato, S. (2013) · IMT Institutional Repository (IMT School for Advanced Studies Lucca) · Cited by 26 · see citing works
Zuo, Z., & Zhao, K. (2020) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24415 · Cited by 25 · see citing works
Commentary: The case for caution in predicting scientists’ future impact
Penner, O., Petersen, A. M., Pan, R. K., & Fortunato, S. (2013) · Physics Today · doi:10.1063/pt.3.1928 · Cited by 25 · see citing works
Citation manipulation through citation mills and pre-print servers
Ibrahim, H., Liu, F., Zaki, Y., & Rahwan, T. (2025) · Scientific Reports · doi:10.1038/s41598-025-88709-7 · Cited by 55 · see citing works
AlShebli, B., Makovi, K., & Rahwan, T. (2020) · Nature Communications · doi:10.1038/s41467-020-20617-y · Cited by 23 · see citing works
RetractedScholarly data mining: A systematic review of its applications
Dridi, A., Gaber, M. M., Azad, R. M. A., & Bhogal, J. (2020) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1395 · Cited by 23 · see citing works
Shaw, J. (2022) · Journal for General Philosophy of Science · doi:10.1007/s10838-021-09575-1 · Cited by 23 · see citing works
What is the best article publishing strategy for early career scientists?
Zhang, Y., & Yu, Q. (2019) · Scientometrics · doi:10.1007/s11192-019-03297-4 · Cited by 23 · see citing works
Characterizing the Impact of Women in Academic IR: A 12-Year Analysis
Xiao, N., Oliveira, D. F. M., & Gupta, R. (2018) · Journal of Vascular and Interventional Radiology · doi:10.1016/j.jvir.2018.06.010 · Cited by 22 · see citing works
The predictability of the Hirsch index evolutionPreprint
Schreiber, M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1307.5964 · Cited by 22 · see citing works
A skeptical view on the Hirsch index and its predictive power*
Schreiber, M. (2018) · Physica Scripta · doi:10.1088/1402-4896/aad959 · Cited by 20 · see citing works
PePSI: Personalized Prediction of Scholars’ Impact in Heterogeneous Temporal Academic Networks
Zhang, J., Xu, B., Liu, J., Tolba, A. K. R., Al-Makhadmeh, Z., & Xia, F. (2018) · IEEE Access · doi:10.1109/access.2018.2863938 · Cited by 21 · see citing works
Heterogeneous dynamical academic network for learning scientific impact propagation
Xu, X., Zhong, T., Li, C., Trajcevski, G., & Zhou, F. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107839 · Cited by 21 · see citing works
Categorization and correlational analysis of quality factors influencing citation
Khatoon, A., Daud, A. Y., & Amjad, T. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-023-10657-3 · Cited by 29 · see citing works
OR Forum—Tenure Analytics: Models for Predicting Research Impact
Bertsimas, D., Brynjolfsson, E., Reichman, S., & Silberholz, J. (2015) · Operations Research · doi:10.1287/opre.2015.1447 · Cited by 21 · see citing works
Researchers’ attitudes towards the h-index on Twitter 2007–2020: criticism and acceptance
Thelwall, M. A., & Kousha, K. (2021) · Scientometrics · doi:10.1007/s11192-021-03961-8 · Cited by 20 · see citing works
Deep forecasting of translational impact in medical research
Nelson, A., Gray, R., Ruffle, J. K., Watkins, H., Herron, D., Sorros, N., Mikhailov, D., Cardoso, M. J., Sebastien Ourselin, A., McNally, N., et al. (2022) · Patterns · doi:10.1016/j.patter.2022.100483 · Cited by 21 · see citing works
Limited validity of equations to predict the future h index
García-Pérez, M. Á. (2013) · Scientometrics · doi:10.1007/s11192-013-0979-7 · Cited by 20 · see citing works
High‐Citation Papers in Space Physics: Examination of Gender, Country, and Paper Characteristics
Moldwin, M. B., & Liemohn, M. W. (2018) · Journal of Geophysical Research Space Physics · doi:10.1002/2018ja025291 · Cited by 20 · see citing works
The emergent integrated network structure of scientific research
Dworkin, J. D., Shinohara, R. T., & Bassett, D. S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216146 · Cited by 21 · see citing works
Large-scale analysis of micro-level citation patterns reveals nuanced selection criteria
Poncela-Casasnovas, J., Gerlach, M., Aguirre, N., & Amaral, L. A. N. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0585-7 · Cited by 20 · see citing works
Evans, J. A. (2013) · Science · doi:10.1126/science.1245218 · Cited by 20 · see citing works
Social Network Analysis As a Tool for Research Policy
Vanderelst, D. F. (2015) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0004266 · Cited by 19 · see citing works
Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact
Jin, Y., Yuan, S., Shao, Z., Hall, W., & Tang, J. (2021) · Scientometrics · doi:10.1007/s11192-020-03860-4 · Cited by 18 · see citing works
Predicting authors’ citation counts and h-indices with a neural network
Mistele, T., Price, T., & Hossenfelder, S. (2019) · Scientometrics · doi:10.1007/s11192-019-03110-2 · Cited by 18 · see citing works
A Deep Learning Methodology for Citation Count Prediction with Large-scale Biblio-Features
Li, M., Xu, J., Ge, B., Liu, J., Jiang, J., & Zhao, Q. (2019) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2019.8913961 · Cited by 18 · see citing works
A better alternative to the h index
Bornmann, L. (2012) · Journal of Informetrics · doi:10.1016/j.joi.2012.09.004 · Cited by 17 · see citing works
- Authors
- Acuna, D. E., Allesina, S., & Kording, K. P.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Acuna, Daniel E.
- Venue
- Nature
- Published
- 2012-09-12
- Volume
- 489
- Issue
- 7415
- Pages
- 201-202
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3770471
- OpenAlex
- W1968900087
- Cited by
- 249
- References
- 7
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 6 · 2023: 14 · 2022: 22 · 2021: 20 · 2020: 21 · 2019: 23 · 2018: 16 · 2017: 19 · 2016: 21 · 2015: 19 · 2014: 21 · 2013: 22 · 2012: 7
- FWCI
- 25.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health (UL1TR000150)
- National Institute of Neurological Disorders and Stroke (R01NS063399)
- National Center for Advancing Translational Sciences
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Physical Sciences › Computer Science › Information Systems › Web visibility and informetrics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- h-index, research productivity, citation impact, life scientists, bibliometric analysis
- MeSH terms
- Animals, Drosophila melanogaster, Biological Evolution, Forecasting, Job Application, Research Personnel, Bibliometrics, Peer Review, Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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