T. Crawshaw

1.8k citations
37 papers · 1.1k · h-index 22

Impact in

Papers in

    • Tuberculosis Research and Epidemiology 20
    • Viral gastroenteritis research and epidemiology 9
    • Mycobacterium research and diagnosis 20

T. Crawshaw

35 papers receiving 993 citations

Peers

T. Crawshaw
Comparison fields: 5 of 53
  • Infectious Diseases 744
  • Agronomy and Crop Science 256
  • Microbiology 137
  • Epidemiology 600
  • Small Animals 134
Replace Sarah Albini with:
Sarah Albini Switzerland
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Hidekazu Niwa Japan
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Abdulwahed Ahmed Hassan Germany
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Citations per field
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Citations per year

Countries citing papers authored by T. Crawshaw

Since Specialization
Citations

This map shows the geographic impact of T. Crawshaw'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 T. Crawshaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Crawshaw more than expected).

Fields of papers citing papers by T. Crawshaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201176
2 199467
3 200966
4 200765
5 200859
6 200957
7 201151
8 201550
9 200848
10 201344
11 201343
12 201142
13 201738
14
Detection of antibodies to influenza A virus in cattle in association with respiratory disease and reduced milk yield.
199833
15 201728
16 201226
17 199925
18 200324
19 200724
20 200721

About T. Crawshaw

T. Crawshaw is a scholar working on Infectious Diseases, Epidemiology, Small Animals, Agronomy and Crop Science and Microbiology, having authored 37 papers that have together received 1.1k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (20 papers), Mycobacterium research and diagnosis (20 papers), Viral gastroenteritis research and epidemiology (9 papers), Microbial infections and disease research (6 papers), Animal Disease Management and Epidemiology (6 papers), Salmonella and Campylobacter epidemiology (5 papers), Diagnosis and treatment of tuberculosis (3 papers) and Animal Nutrition and Physiology (3 papers). The work is most often cited by research in Infectious Diseases (744 citations), Agronomy and Crop Science (256 citations), Microbiology (137 citations), Epidemiology (600 citations) and Small Animals (134 citations). T. Crawshaw has collaborated with scholars based in United Kingdom, Australia and New Zealand. Frequent co-authors include R. Clifton‐Hadley, Mark A. Chambers, R. Glyn Hewinson, Ian H. Brown, R. de la Rúa-Domènech, Dipesh Davé, Deanna Dalley, Darren J. Shaw, Danièlle Gunn‐Moore and N. H. Smith. Their work appears in journals such as Veterinary Record, The Veterinary Journal, Journal of Clinical Microbiology, New Zealand Veterinary Journal and Frontiers in Cellular and Infection Microbiology.

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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