G Férard

1.9k citations
100 papers · 1.5k indexed · h-index 18

G Férard

92 papers receiving 1.4k citations

Peers

G Férard
Comparison fields: 5 of 132
  • Clinical Biochemistry 110
  • Statistics, Probability and Uncertainty 98
  • Physiology 328
  • Endocrinology, Diabetes and Metabolism 191
  • Nephrology 81
Replace F.-Javier Gella with:
F.-Javier Gella Spain
Rainer Klauke Germany
R Bonora Italy
Paul Franck Netherlands
C. A. Ferrero Italy
Won‐Ki Min South Korea
N. Kristiansen Germany
Wieland Hoelzel Germany
Donald R. Wybenga United States
C A Burtis United States
G Férard relative to F.-Javier Gella Spain F.-Javier Gella's profile →
Citations per field
00.5×1.5×
F.-Javier Gella · 1×
Citations per year

Countries citing papers authored by G Férard

Since Specialization
Citations

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

Fields of papers citing papers by G Férard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20165
2 20112
3 20093
4 200631
5 200613
6 20043
7
Le calibrage en enzymologie clinique : principe, conditions d'application et résultats
20020
8 200247
9 200110
10 19983
11 199811
12 19983
13 199716
14 199510
15 19948
16 19920
17 19921
18 19905
19 198911
20 198710

About G Férard

G Férard is a scholar working on Clinical Biochemistry, Endocrinology, Diabetes and Metabolism, Physiology, Nephrology and Physical and Theoretical Chemistry, having authored 100 papers that have together received 1.5k indexed citations. Recurring topics across this work include Clinical Laboratory Practices and Quality Control (15 papers), Diabetes Management and Research (9 papers), Analytical Chemistry and Chromatography (8 papers), Metabolism and Genetic Disorders (8 papers), Pancreatic function and diabetes (7 papers), Pesticide Residue Analysis and Safety (6 papers), Diabetes and associated disorders (6 papers) and Biomedical Text Mining and Ontologies (6 papers). The work is most often cited by research in Clinical Biochemistry (110 citations), Statistics, Probability and Uncertainty (98 citations), Physiology (328 citations), Endocrinology, Diabetes and Metabolism (191 citations) and Nephrology (81 citations). G Férard has collaborated with scholars based in France, Germany and Denmark. Frequent co-authors include Takashi Kanno, F.-Javier Gella, Ferruccio Ceriotti, Ibrahima Sall, Poul J. Jørgensen, C. A. Ferrero, Wieland Hoelzel, Paul Franck, N. Kristiansen and R Bonora. Their work appears in journals such as Clinical Chemistry and Laboratory Medicine (CCLM), Clinica Chimica Acta, Clinical Chemistry, Pure and Applied Chemistry and Pflügers Archiv - European Journal of Physiology.

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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