Catalina March
About
In The Last Decade
Catalina March
8 papers receiving 574 citations
Peers
Comparison fields: 5 of 66
- Molecular Medicine 315
- Molecular Biology 185
- Endocrinology 162
- Immunology 135
- Epidemiology 128
Countries citing papers authored by Catalina March
This map shows the geographic impact of Catalina March'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 Catalina March with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Catalina March more than expected).
Fields of papers citing papers by Catalina March
This network shows the impact of papers produced by Catalina March. 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 Catalina March. The network helps show where Catalina March may publish in the future.
Co-authorship network of co-authors of Catalina March
This figure shows the co-authorship network connecting the top 25 collaborators of Catalina March. A scholar is included among the top collaborators of Catalina March 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 Catalina March. Catalina March is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 105 | |
| 2 | 104 | |
| 3 | 66 | |
| 4 | 25 | |
| 5 | 60 | |
| 6 | 57 | |
| 7 | 92 | |
| 8 | 71 |
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.