Self-rankings as a predictor of scientific impact beyond peer review
- DOI
- 10.1038/s43588-026-01039-0
- Published
- 2026-08-24
- Container
- Nature Computational Science
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1038/s43588-026-01039-0,
title = {Self-rankings as a predictor of scientific impact beyond peer review},
author = {Buxin Su and Natalie Collina and Garrett Wen and Didong Li and Kyunghyun Cho and Jianqing Fan and Bingxin Zhao and Weijie Su},
year = {2026},
journal = {Nature Computational Science},
doi = {10.1038/s43588-026-01039-0},
url = {https://doi.org/10.1038/s43588-026-01039-0}
}RIS
TY - JOUR TI - Self-rankings as a predictor of scientific impact beyond peer review AU - Buxin Su AU - Natalie Collina AU - Garrett Wen AU - Didong Li AU - Kyunghyun Cho AU - Jianqing Fan AU - Bingxin Zhao AU - Weijie Su PY - 2026 JO - Nature Computational Science DO - 10.1038/s43588-026-01039-0 UR - https://doi.org/10.1038/s43588-026-01039-0 ER -
APA
Su, B., Collina, N., Wen, G., Li, D., Cho, K., Fan, J., Zhao, B., & Su, W. (2026). Self-rankings as a predictor of scientific impact beyond peer review. Nature Computational Science. https://doi.org/10.1038/s43588-026-01039-0
Source records
- crossref · retrieved 2026-11-10T14:13:54.684Z