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.
Countries citing papers authored by Alex Gammerman
Since
Specialization
Citations
This map shows the geographic impact of Alex Gammerman'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 Alex Gammerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Gammerman more than expected).
This network shows the impact of papers produced by Alex Gammerman. 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 Alex Gammerman. The network helps show where Alex Gammerman may publish in the future.
Co-authorship network of co-authors of Alex Gammerman
This figure shows the co-authorship network connecting the top 25 collaborators of Alex Gammerman.
A scholar is included among the top collaborators of Alex Gammerman 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 Alex Gammerman. Alex Gammerman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Vovk, Vladimir, Ilia Nouretdinov, & Alex Gammerman. (2003). Testing exchangeability on-line. International Conference on Machine Learning. 768–775.38 indexed citations
10.
Delft, Frederik W. van, Anthony Bellotti, Naina Patel, et al.. (2003). Gene expression profiling in childhood acute leukaemia; a useful classification tool and a first promising insight into drug resistance.. Blood. 102(11).1 indexed citations
Papadopoulos, Harris, et al.. (2002). Inductive Confidence Machines for Regression.. Annals of Mathematics and Artificial Intelligence.1 indexed citations
13.
Nouretdinov, Ilia, et al.. (2002). Transductive Confidence Machines for Pattern Recognition.. Annals of Mathematics and Artificial Intelligence.2 indexed citations
14.
Papadopoulos, Harris, Vladimir Vovk, & Alex Gammerman. (2002). Qualified Prediction for Large Data Sets in the Case of Pattern Recognition.. 159–163.20 indexed citations
Saunders, Craig, Alex Gammerman, & Vladimir Vovk. (1999). Transduction with Confidence and Credibility. ePrints Soton (University of Southampton). 722–726.85 indexed citations
17.
Vovk, Vladimir, Alex Gammerman, & Craig Saunders. (1999). Machine-Learning Applications of Algorithmic Randomness. ePrints Soton (University of Southampton). 444–453.83 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.