Jay Clausen

1.4k total citations
48 papers, 933 citations indexed

About

Jay Clausen is a scholar working on Pollution, Health, Toxicology and Mutagenesis and Artificial Intelligence. According to data from OpenAlex, Jay Clausen has authored 48 papers receiving a total of 933 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Pollution, 18 papers in Health, Toxicology and Mutagenesis and 10 papers in Artificial Intelligence. Recurrent topics in Jay Clausen's work include Heavy metals in environment (14 papers), Geochemistry and Geologic Mapping (9 papers) and Toxic Organic Pollutants Impact (9 papers). Jay Clausen is often cited by papers focused on Heavy metals in environment (14 papers), Geochemistry and Geologic Mapping (9 papers) and Toxic Organic Pollutants Impact (9 papers). Jay Clausen collaborates with scholars based in United States, Australia and Italy. Jay Clausen's co-authors include Nic Korte, Benjamín C. Bostick, Liyuan Liang, Gerald E. Speitel, Hiroshi Yamamoto, Jing Sun, Joshua D. Landis, Teofilo A. Abrajano, Linnea J. Heraty and Neil C. Sturchio and has published in prestigious journals such as Environmental Science & Technology, The Science of The Total Environment and Environmental Pollution.

In The Last Decade

Jay Clausen

42 papers receiving 837 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jay Clausen United States 14 349 320 169 142 114 48 933
Marie‐Pierre Isaure France 22 210 0.6× 596 1.9× 76 0.4× 111 0.8× 106 0.9× 46 1.9k
Amauri Antônio Menegário Brazil 21 327 0.9× 326 1.0× 69 0.4× 136 1.0× 94 0.8× 103 1.4k
Petr S. Fedotov Russia 20 285 0.8× 543 1.7× 136 0.8× 66 0.5× 55 0.5× 93 1.3k
Steffen Kümmel Germany 18 293 0.8× 368 1.1× 113 0.7× 53 0.4× 59 0.5× 70 956
Grethe Wibetoe Norway 22 388 1.1× 212 0.7× 62 0.4× 99 0.7× 45 0.4× 54 1.4k
Zeming Shi China 19 300 0.9× 238 0.7× 91 0.5× 177 1.2× 33 0.3× 58 1.2k
Anat Bernstein Israel 15 365 1.0× 405 1.3× 135 0.8× 72 0.5× 113 1.0× 36 831
Paul M. McGinley United States 7 451 1.3× 482 1.5× 102 0.6× 99 0.7× 443 3.9× 15 1.3k
Yiling Chen China 17 132 0.4× 171 0.5× 188 1.1× 88 0.6× 77 0.7× 37 924
Tea Zuliani Slovenia 22 533 1.5× 434 1.4× 99 0.6× 51 0.4× 50 0.4× 69 1.3k

Countries citing papers authored by Jay Clausen

Since Specialization
Citations

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

Fields of papers citing papers by Jay Clausen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jay Clausen

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Clausen. A scholar is included among the top collaborators of Jay Clausen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jay Clausen. Jay Clausen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Truong, Van‐Anh, et al.. (2024). Improvements in Target Detection Using Machine Learning. 28. 1–2. 1 indexed citations
2.
Scircle, Austin, Samuel Beal, Jay Clausen, et al.. (2023). Validation and standardization of SPE and HPLC-UV methods for simultaneous determination of legacy and insensitive munitions. Environmental Nanotechnology Monitoring & Management. 20. 100837–100837. 2 indexed citations
3.
4.
Crouch, Rebecca A., Samuel Beal, Guilherme R. Lotufo, et al.. (2020). Methods for simultaneous determination of legacy and insensitive munition (IM) constituents in aqueous, soil/sediment, and tissue matrices. Talanta. 217. 121008–121008. 7 indexed citations
5.
Barker, Amanda, et al.. (2020). Environmental impact of metals resulting from military training activities: A review. Chemosphere. 265. 129110–129110. 27 indexed citations
6.
Clausen, Jay, et al.. (2017). Applying Incremental Sampling Methodology to Soils Containing Heterogeneously Distributed Metallic Residues to Improve Risk Analysis. Bulletin of Environmental Contamination and Toxicology. 100(1). 155–161. 5 indexed citations
7.
Moser, Robert D., et al.. (2014). Laboratory Evaluation of Expedient Low-Temperature Admixtures for Runway Craters in Cold Weather. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 1 indexed citations
8.
Clausen, Jay, et al.. (2013). Incremental Sampling Methodology (ISM) for Metallic Residues. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 1 indexed citations
9.
Clausen, Jay, et al.. (2013). Cost and Performance Report of Incremental Sampling Methodology for Soil Containing Metallic Residues. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 2 indexed citations
10.
Clausen, Jay, et al.. (2013). Demonstration of Incremental Sampling Methodology for Soil Containing Metallic Residues. Journal of Insect Physiology. 12(7). 731–40. 6 indexed citations
11.
Clausen, Jay, et al.. (2012). Evaluation of sampling and sample preparation modifications for soil containing metallic residues. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 7 indexed citations
12.
Clausen, Jay, Benjamín C. Bostick, Anthony J. Bednar, Jing Sun, & Joshua D. Landis. (2011). Tungsten Speciation in Firing Range Soils. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 11 indexed citations
13.
Parker, Louise V., et al.. (2011). Demonstration/Validation of the Snap Sampler Passive Groundwater Sampling Device at the Former McClellan Air Force Base. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 1 indexed citations
14.
Clausen, Jay, et al.. (2010). Adsorption/Desorption Measurements of Nitroglycerin and Dinitrotoluene in Camp Edwards, Massachusetts Soil. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 11 indexed citations
15.
16.
Clausen, Jay & Nic Korte. (2009). Environmental fate of tungsten from military use. The Science of The Total Environment. 407(8). 2887–2893. 74 indexed citations
17.
Clausen, Jay, et al.. (2007). Environmental assessment of lead at Camp Edwards, Massachusetts, small arms ranges. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 2 indexed citations
18.
Clausen, Jay, Susan Taylor, Steven L. Larson, et al.. (2007). Fate and Transport of Tungsten at Camp Edwards Small Arms Ranges. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 22 indexed citations
19.
Pennington, Judith C., Thomas F. Jenkins, Sonia Thiboutot, et al.. (2006). Distribution and fate of energetics on DoD test and training ranges : interim report 5. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 54 indexed citations
20.
Clausen, Jay, et al.. (2003). A case study of contaminants on military ranges: Camp Edwards, Massachusetts, USA. Environmental Pollution. 129(1). 13–21. 164 indexed citations

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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