This map shows the geographic impact of Michael Cox'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 Michael Cox with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Cox more than expected).
This network shows the impact of papers produced by Michael Cox. 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 Michael Cox. The network helps show where Michael Cox may publish in the future.
Co-authorship network of co-authors of Michael Cox
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Cox.
A scholar is included among the top collaborators of Michael Cox 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 Michael Cox. Michael Cox is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Michael Cox is a scholar working on Infectious Diseases, Organic Chemistry and Surgery, having authored 3 papers that have together received 503 indexed citations. The work is most often cited by research in Computer Vision and Pattern Recognition (119 citations), Signal Processing (53 citations) and Computer Graphics and Computer-Aided Design (15 citations). Frequent co-authors include Trevor J. Cox and David G. Bostwick. Their work appears in journals such as Gastroenterology.
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.