G. Schumann

64 papers receiving 2.4k citations

Peers

G. Schumann
Comparison fields: 5 of 139
  • Nephrology 610
  • Transplantation 80
  • Statistics, Probability and Uncertainty 191
  • Clinical Biochemistry 129
  • Pharmacology 165
Replace Won‐Ki Min with:
Won‐Ki Min South Korea
Andrew Whelton United States
Linda M. Thienpont Belgium
Rainer Haeckel Germany
Mogens Hørder Denmark
Vladimír Palička Czechia
Matti Mänttäri Finland
Jacobus Ungerer Australia
Rainer Klauke Germany
F.-Javier Gella Spain
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Citations per field
00.5×5.2×
Won‐Ki Min · 1×
Citations per year

Countries citing papers authored by G. Schumann

Since Specialization
Citations

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

Fields of papers citing papers by G. Schumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. Schumann. 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 G. Schumann. The network helps show where G. Schumann may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998313
2 2002308
3 2002220
4 2008206
5 2002120
6 1998118
7 2011101
8 200297
9 199991
10 200781
11 200279
12 200472
13 200267
14 200665
15
Characterization and Qualification of Commutable Reference Materials for Laboratory Medicine - Approved Guideline
201049
16 200147
17 200935
18 200632
19 200532
20 200729

About G. Schumann

G. Schumann is a scholar working on Transplantation, Nephrology, Physiology, Statistics, Probability and Uncertainty and Food Science, having authored 65 papers that have together received 2.5k indexed citations. Recurring topics across this work include Clinical Laboratory Practices and Quality Control (20 papers), Pesticide Residue Analysis and Safety (11 papers), Renal function and acid-base balance (6 papers), Analytical Chemistry and Chromatography (5 papers), Analytical Methods in Pharmaceuticals (4 papers), Scientific Measurement and Uncertainty Evaluation (4 papers), Antibiotics Pharmacokinetics and Efficacy (4 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). The work is most often cited by research in Nephrology (610 citations), Transplantation (80 citations), Statistics, Probability and Uncertainty (191 citations), Clinical Biochemistry (129 citations) and Pharmacology (165 citations). G. Schumann has collaborated with scholars based in Germany, Netherlands and Italy. Frequent co-authors include Rainer Klauke, Johannes Brodehl, Raymund Zinck, Arend Bökenkamp, Ferruccio Ceriotti, D. J. Byrd, Mauro Panteghini, Poul J. Jørgensen, F.-Javier Gella and Paul Franck. Their work appears in journals such as Clinical Chemistry and Laboratory Medicine (CCLM), Clinica Chimica Acta, Clinical Chemistry, Analytical and Bioanalytical Chemistry and Journal of Proteome Research.

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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