Jack L. Warner

801 citations
11 papers · 515 · h-index 8

Impact in

Papers in

Jack L. Warner

11 papers receiving 462 citations

Peers

Jack L. Warner
Comparison fields: 5 of 106
  • Health, Toxicology and Mutagenesis 158
  • Atmospheric Science 183
  • Statistics and Probability 74
  • Environmental Engineering 95
  • Automotive Engineering 51
Replace Daniel C. Neale with:
Daniel C. Neale United States
Dennis R. Ridley United States
Pierre Chaussé France
Robin T. Shealy United States
Rebecca Wilson United Kingdom
Eleanor O’Rourke United States
Gavino Puggioni United States
Francesco Lagona Italy
María del Mar López‐Martín Spain
Jack L. Warner relative to Daniel C. Neale United States Daniel C. Neale's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jack L. Warner

Since Specialization
Citations

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

Fields of papers citing papers by Jack L. Warner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack L. Warner. 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 Jack L. Warner. The network helps show where Jack L. Warner may publish in the future.

Co-authors

The 10 scholars most cited alongside Jack L. Warner, 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 Jack L. Warner Line = papers co-authored together Jack L. Warner links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 1974179
2 198498
3 197198
4 197952
5 197443
6 197714
7 197611
8 19848
9 20196
10 20045
11 20221

About Jack L. Warner

Jack L. Warner is a scholar working on Health, Toxicology and Mutagenesis, Automotive Engineering, Public Health, Environmental and Occupational Health, Applied Psychology and Atmospheric Science, having authored 11 papers that have together received 515 indexed citations. Recurring topics across this work include Air Quality and Health Impacts (4 papers), Air Quality Monitoring and Forecasting (2 papers), Vehicle emissions and performance (2 papers), Atmospheric chemistry and aerosols (2 papers), Human Resource Development and Performance Evaluation (2 papers), Impact of Light on Environment and Health (2 papers), Behavioral and Psychological Studies (1 paper) and Malaria Research and Control (1 paper). The work is most often cited by research in Health, Toxicology and Mutagenesis (158 citations), Atmospheric Science (183 citations), Statistics and Probability (74 citations), Environmental Engineering (95 citations) and Automotive Engineering (51 citations). Jack L. Warner has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include William S. Cleveland, Beat Kleiner, T. E. Graedel, R. Gnanadesikan, David Andrews, John H. Flowers, John W. Williams, Chuan Li, Baoling Ma and Karen McKenzie. Their work appears in journals such as Science, Journal of Applied Psychology, Memory & Cognition, Mathematical Biosciences and Biometrics.

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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