Mercè Ibarz

1.4k citations
44 papers · 807 · h-index 17

Impact in

Papers in

Mercè Ibarz

39 papers receiving 774 citations

Peers

Mercè Ibarz
Comparison fields: 5 of 98
  • Statistics, Probability and Uncertainty 183
  • Physiology 438
  • Family Practice 23
  • Nephrology 91
  • Medical Laboratory Technology 16
Replace Edward T. Wong with:
Edward T. Wong United States
Josep Miquel Bauçà Spain
Josep M. Queraltó Spain
P M Broughton United Kingdom
Douglas Chesher Australia
Christiane Oddoze France
Bianca Hemmingsen Denmark
Gian Carlo Zucchelli Italy
Natsu Fukui United States
Ruth L. Coleman United Kingdom
Mercè Ibarz relative to Edward T. Wong United States Edward T. Wong's profile →
Citations per field
00.5×10×15.4×
Edward T. Wong · 1×
Citations per year

Countries citing papers authored by Mercè Ibarz

Since Specialization
Citations

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

Fields of papers citing papers by Mercè Ibarz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011143
2 2014103
3 201651
4 201146
5 201843
6 201642
7 201938
8 201837
9 200831
10 201628
11 201425
12 200921
13 201621
14 201920
15 200819
16 201018
17 201316
18 201814
19 202013
20 202212

About Mercè Ibarz

Mercè Ibarz is a scholar working on Physiology, Statistics, Probability and Uncertainty, Nephrology, General Health Professions and Surgery, having authored 44 papers that have together received 807 indexed citations. Recurring topics across this work include Clinical Laboratory Practices and Quality Control (25 papers), Meta-analysis and systematic reviews (7 papers), Healthcare cost, quality, practices (5 papers), Reliability and Agreement in Measurement (3 papers), Acute Kidney Injury Research (3 papers), Parathyroid Disorders and Treatments (3 papers), Amino Acid Enzymes and Metabolism (2 papers) and Hemodynamic Monitoring and Therapy (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (183 citations), Physiology (438 citations), Family Practice (23 citations), Nephrology (91 citations) and Medical Laboratory Technology (16 citations). Mercè Ibarz has collaborated with scholars based in Spain, United Kingdom and Italy. Frequent co-authors include Michael P. Cornes, Giuseppe Lippi, Ana-Maria Šimundić, Mads Nybo, Kjell Grankvist, Gunn B.B. Kristensen, José Manuel Valdivielso, Milica Božić, Petya Valcheva and Elvira Fernández. Their work appears in journals such as Clinical Chemistry and Laboratory Medicine (CCLM), Biochemia Medica, Nutrients, Diagnosis and Clinical Kidney Journal.

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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