M.Clara Sañudo-Peña
About
In The Last Decade
M.Clara Sañudo-Peña
16 papers receiving 2.8k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| M.Clara Sañudo-Peña United States | 13 | 2.6k | 2.1k | 758 | 339 | 281 | 16 | 2.9k | ||
| Heike Hermann Germany | 9 | 3.0k 1.1× | 2.2k 1.0× | 1.1k 1.4× | 315 0.9× | 355 1.3× | 10 | 3.6k | ||
| A B Lynn United States | 7 | 3.6k 1.4× | 2.7k 1.3× | 981 1.3× | 602 1.8× | 258 0.9× | 7 | 4.1k | ||
| Kang Tsou United States | 19 | 1.9k 0.7× | 1.6k 0.7× | 424 0.6× | 234 0.7× | 499 1.8× | 29 | 2.3k | ||
| Sara González Spain | 21 | 2.0k 0.8× | 1.5k 0.7× | 352 0.5× | 246 0.7× | 183 0.7× | 43 | 2.4k | ||
| K Tsou China | 12 | 1.7k 0.7× | 1.7k 0.8× | 638 0.8× | 277 0.8× | 485 1.7× | 23 | 2.3k | ||
| Astrid Cannich France | 19 | 2.3k 0.9× | 1.6k 0.7× | 729 1.0× | 395 1.2× | 382 1.4× | 36 | 3.0k | ||
| T. P. Dinh United States | 7 | 2.1k 0.8× | 1.3k 0.6× | 606 0.8× | 219 0.6× | 233 0.8× | 7 | 2.3k | ||
| Darren Fegley United States | 9 | 2.4k 0.9× | 1.5k 0.7× | 603 0.8× | 269 0.8× | 346 1.2× | 10 | 2.8k | ||
| Rosario de Miguel Spain | 31 | 1.8k 0.7× | 1.5k 0.7× | 336 0.4× | 368 1.1× | 114 0.4× | 50 | 2.4k | ||
| Daniela Viganò Italy | 32 | 2.3k 0.9× | 2.1k 1.0× | 505 0.7× | 249 0.7× | 222 0.8× | 38 | 3.0k |
Countries citing papers authored by M.Clara Sañudo-Peña
This map shows the geographic impact of M.Clara Sañudo-Peña'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 M.Clara Sañudo-Peña with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.Clara Sañudo-Peña more than expected).
Fields of papers citing papers by M.Clara Sañudo-Peña
This network shows the impact of papers produced by M.Clara Sañudo-Peña. 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 M.Clara Sañudo-Peña. The network helps show where M.Clara Sañudo-Peña may publish in the future.
Co-authorship network of co-authors of M.Clara Sañudo-Peña
This figure shows the co-authorship network connecting the top 25 collaborators of M.Clara Sañudo-Peña. A scholar is included among the top collaborators of M.Clara Sañudo-Peña 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 M.Clara Sañudo-Peña. M.Clara Sañudo-Peña is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
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.