Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average within
it), or reaches the top citation threshold in at least one of its specific research topics.
This map shows the geographic impact of C. Spearman'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 C. Spearman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Spearman more than expected).
This network shows the impact of papers produced by C. Spearman. 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 C. Spearman. The network helps show where C. Spearman may publish in the future.
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All Works
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C. Spearman is a scholar working on Infectious Diseases, Organic Chemistry, Surgery, Communication and Small Animals, having authored 2 papers that have together received 1.9k indexed citations. The work is most often cited by research in Statistics and Probability (84 citations), Management Science and Operations Research (106 citations), Cognitive Neuroscience (165 citations), Experimental and Cognitive Psychology (108 citations) and Artificial Intelligence (224 citations). Their work appears in journals such as International Journal of Epidemiology and PubMed.
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.