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-authors
The 2 scholars most cited alongside Michael Cox, linked wherever they
have co-authored with each other. Click a name or a connecting line to browse the papers
they share.
Border = papers with Michael CoxLine = papers co-authored togetherMichael Cox links everyone, so they are left out of the graph.
Michael Cox is a scholar working on Infectious Diseases, Organic Chemistry, Surgery, Communication and Small Animals, 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), Computer Graphics and Computer-Aided Design (15 citations), Artificial Intelligence (124 citations) and Computational Mathematics (2 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.