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.
Epidemiological evidence for causal relationship between Epstein-Barr virus and Burkitt's lymphoma from Ugandan prospective study
1978419 citationsG de-Thé, A. Geser et al.Natureprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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This map shows the geographic impact of A. Geser'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 A. Geser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Geser more than expected).
This network shows the impact of papers produced by A. Geser. 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 A. Geser. The network helps show where A. Geser may publish in the future.
Co-authorship network of co-authors of A. Geser
This figure shows the co-authorship network connecting the top 25 collaborators of A. Geser.
A scholar is included among the top collaborators of A. Geser 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 A. Geser. A. Geser is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Draper, C. C., G. Brubaker, A. Geser, V.A.E.B. Kilimali, & W. H. Wernsdorfer. (1985). Serial studies on the evolution of chloroquine resistance in an area of East Africa receiving intermittent malaria chemosuppression.. PubMed. 63(1). 109–18.35 indexed citations
4.
Geser, A. & G. Brubaker. (1985). A preliminary report of epidemiological studies of Burkitt's lymphoma, Epstein-Barr virus infection and malaria in North Mara, Tanzania.. PubMed. 205–15.7 indexed citations
Geser, A., et al.. (1980). The frequency of Epstein-Barr virus infection and Burkitt's lymphoma at high and low altitudes in East Africa.. PubMed. 28(3). 307–21.7 indexed citations
10.
Geser, A., et al.. (1978). Environmental factors in the etiology of nasopharyngeal carcinoma: report on a case-control study in Hong Kong.. PubMed. 213–29.48 indexed citations
11.
de-Thé, G, A. Geser, Nicholas Day, et al.. (1978). Epidemiological evidence for causal relationship between Epstein-Barr virus and Burkitt's lymphoma from Ugandan prospective study. Nature. 274(5673). 756–761.419 indexed citations breakdown →
de-Thé, G, Day Ne, A. Geser, et al.. (1975). Sero-epidemiology of the Epstein-Barr virus: preliminary analysis of an international study - a review.. PubMed. 3–16.99 indexed citations
Geser, A., Nicholas Day, G de-Thé, et al.. (1974). The variability in immunofluorescent viral capsid antigen antibody tests in population surveys of Epstein-Barr virus infections.. PubMed. 50(5). 389–400.5 indexed citations
Zykov, M. P., et al.. (1966). A serological test in tuberculosis. A "blind" trial of the kaolin-agglutination test (KAT) for detection of tuberculosis antibodies.. PubMed. 35(4). 581–92.1 indexed citations
19.
Narain, Raj, et al.. (1963). SOME ASPECTS OF A TUBERCULOSIS PREVALENCE SURVEY IN A SOUTH INDIAN DISTRICT.. PubMed. 29. 641–64.25 indexed citations
20.
Narain, Raj, et al.. (1963). Tuberculosis prevalence survey in Tumkur district.11 indexed citations
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.