Gina‐Maria Pomann

471 citations
41 papers · 259 · h-index 9

Impact in

Papers in

    • Statistics Education and Methodologies 7
    • Statistical Methods and Inference 3
    • Statistical Methods and Bayesian Inference 2
    • Genetics, Bioinformatics, and Biomedical Research 5

Gina‐Maria Pomann

34 papers receiving 255 citations

Peers

Gina‐Maria Pomann
Comparison fields: 5 of 74
  • Statistics and Probability 56
  • Statistics, Probability and Uncertainty 12
  • Computational Mathematics 1
  • Information Systems and Management 10
  • Physiology 33
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Citations per field
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Citations per year

Countries citing papers authored by Gina‐Maria Pomann

Since Specialization
Citations

This map shows the geographic impact of Gina‐Maria Pomann'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 Gina‐Maria Pomann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gina‐Maria Pomann more than expected).

Fields of papers citing papers by Gina‐Maria Pomann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gina‐Maria Pomann. 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 Gina‐Maria Pomann. The network helps show where Gina‐Maria Pomann may publish in the future.

Co-authors

The 25 scholars most cited alongside Gina‐Maria Pomann, 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 Gina‐Maria Pomann Line = papers co-authored together Gina‐Maria Pomann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201738
2 201638
3 201933
4 201818
5 201712
6 201912
7 202011
8 20169
9 20218
10 20198
11 20186
12 20205
13 20235
14 20225
15 20225
16 20225
17 20195
18 20194
19 20194
20 20153

About Gina‐Maria Pomann

Gina‐Maria Pomann is a scholar working on Statistics and Probability, Molecular Biology, Public Health, Environmental and Occupational Health, Surgery and Biomedical Engineering, having authored 41 papers that have together received 259 indexed citations. Recurring topics across this work include Statistics Education and Methodologies (7 papers), Genetics, Bioinformatics, and Biomedical Research (5 papers), Health and Medical Research Impacts (4 papers), Interdisciplinary Research and Collaboration (3 papers), Statistical Methods and Inference (3 papers), Biomedical and Engineering Education (3 papers), Pediatric Urology and Nephrology Studies (2 papers) and Statistical Methods and Bayesian Inference (2 papers). The work is most often cited by research in Statistics and Probability (56 citations), Statistics, Probability and Uncertainty (12 citations), Computational Mathematics (1 citation), Information Systems and Management (10 citations) and Physiology (33 citations). Gina‐Maria Pomann has collaborated with scholars based in United States, Germany and Singapore. Frequent co-authors include Ana‐Maria Staicu, Sujit K. Ghosh, Wolfgang C. Winkelmayer­, Benjamin A. Goldstein, Steven Wolf, Jonathan C. Routh, John S. Wiener, Kishan S. Parikh, Jesse D. Troy and J. Todd Purves. Their work appears in journals such as Disability and health journal, Statistics in Medicine, Journal of Pediatric Urology, Journal of Reconstructive Microsurgery and Academic Medicine.

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.

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