Mark Chu

14 papers receiving 801 citations

Peers

Mark Chu
Comparison fields: 5 of 93
  • Toxicology 534
  • Pharmacology 432
  • Safety, Risk, Reliability and Quality 176
  • Pathology and Forensic Medicine 206
  • Physical Therapy, Sports Therapy and Rehabilitation 46
Replace Michael D. Robertson with:
Michael D. Robertson Australia
Marie Longo Australia
Edward Ogden Australia
B. E. Smink Netherlands
Martin Boorman Australia
Stig Tore Bogstrand Norway
R.J. Lokan Australia
Mpm Mathijssen Netherlands
Marcelline Burns United States
Andrew Spurgin United States
Mark Chu relative to Michael D. Robertson Australia Michael D. Robertson's profile →
Citations per field
00.5×1.5×2.1×
Michael D. Robertson · 1×
Citations per year

Countries citing papers authored by Mark Chu

Since Specialization
Citations

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

Fields of papers citing papers by Mark Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Mark Chu, 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 Mark Chu Line = papers co-authored together Mark Chu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2003386
2 2003209
3 2007102
4 201553
5 201147
6 200237
7 201625
8 202015
9 19966
10 20143
11 19982
12
Giallo sarai tu! Hegemonic representations and limits of heteroglossia in Carlo Lucarelli
20161
13 19961
14 20141
15 20001
16 20141
17 20190
18 19920
19 20000
20 19920

About Mark Chu

Mark Chu is a scholar working on Toxicology, Pharmacology, Sociology and Political Science, Pathology and Forensic Medicine and Artificial Intelligence, having authored 20 papers that have together received 890 indexed citations. Recurring topics across this work include Forensic Toxicology and Drug Analysis (7 papers), Cannabis and Cannabinoid Research (6 papers), Italian Fascism and Post-war Society (5 papers), Alcohol Consumption and Health Effects (4 papers), Historical Economic and Social Studies (2 papers), Linguistic Studies and Language Acquisition (2 papers), Cardiac Arrest and Resuscitation (2 papers) and Psychedelics and Drug Studies (1 paper). The work is most often cited by research in Toxicology (534 citations), Pharmacology (432 citations), Safety, Risk, Reliability and Quality (176 citations), Pathology and Forensic Medicine (206 citations) and Physical Therapy, Sports Therapy and Rehabilitation (46 citations). Mark Chu has collaborated with scholars based in Australia, Ireland and France. Frequent co-authors include Olaf H. Drummer, Dimitri Gerostamoulos, Philip Swann, Michael D. Robertson, John R. M. Caplehorn, Martin Boorman, Luke N. Rodda, Dan I. Lubman, Morris Odell and Jochen Beyer. Their work appears in journals such as Italian Studies, Forensic Science International, Journal of Analytical Toxicology, Accident Analysis & Prevention and Analytical and Bioanalytical Chemistry.

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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