Cristina Rea
About
In The Last Decade
Cristina Rea
35 papers receiving 621 citations
Peers
Comparison fields: 5 of 51
- Nuclear and High Energy Physics 473
- Aerospace Engineering 186
- Artificial Intelligence 147
- Materials Chemistry 137
- Astronomy and Astrophysics 112
Countries citing papers authored by Cristina Rea
This map shows the geographic impact of Cristina Rea's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cristina Rea with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cristina Rea more than expected).
Fields of papers citing papers by Cristina Rea
This network shows the impact of papers produced by Cristina Rea. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cristina Rea. The network helps show where Cristina Rea may publish in the future.
Co-authorship network of co-authors of Cristina Rea
This figure shows the co-authorship network connecting the top 25 collaborators of Cristina Rea. A scholar is included among the top collaborators of Cristina Rea based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cristina Rea. Cristina Rea is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 7 | |
| 8 | 14 | |
| 9 | 2 | |
| 10 | 14 | |
| 11 | 6 | |
| 12 | 1 | |
| 13 | 40 | |
| 14 | 21 | |
| 15 | 45 | |
| 16 | 30 | |
| 17 | Interpretable data-driven disruption predictors to trigger avoidance and mitigation actuators on different tokamaks | 1 |
| 18 | 27 | |
| 19 | Quantifying and Propagating Uncertainties to Enhance Real-time Disruption Prediction with Machine Learning | 1 |
| 20 | 5 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.