This map shows the geographic impact of Thomas Bayes'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 Thomas Bayes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Bayes more than expected).
This network shows the impact of papers produced by Thomas Bayes. 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 Thomas Bayes. The network helps show where Thomas Bayes may publish in the future.
Co-authorship network of co-authors of Thomas Bayes
This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Bayes.
A scholar is included among the top collaborators of Thomas Bayes 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 Thomas Bayes. Thomas Bayes is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Thomas Bayes is a scholar working on Infectious Diseases, Organic Chemistry and Surgery, having authored 3 papers that have together received 599 indexed citations. The work is most often cited by research in Statistics and Probability (68 citations), Statistics, Probability and Uncertainty (45 citations) and General Decision Sciences (9 citations). Frequent co-authors include G. A. Barnard. Their work appears in journals such as Biometrika and Resonance.
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.