Rachel M. Tell

909 total citations · 1 hit paper
5 papers, 448 citations indexed

About

Rachel M. Tell is a scholar working on Infectious Diseases, Cardiology and Cardiovascular Medicine and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Rachel M. Tell has authored 5 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Infectious Diseases, 1 paper in Cardiology and Cardiovascular Medicine and 1 paper in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Rachel M. Tell's work include SARS-CoV-2 and COVID-19 Research (3 papers), Viral gastroenteritis research and epidemiology (2 papers) and SARS-CoV-2 detection and testing (2 papers). Rachel M. Tell is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (3 papers), Viral gastroenteritis research and epidemiology (2 papers) and SARS-CoV-2 detection and testing (2 papers). Rachel M. Tell collaborates with scholars based in United States and Brazil. Rachel M. Tell's co-authors include Mia Kim Torchetti, Suelee Robbe‐Austerman, Melinda Jenkins-Moore, Andrew S. Bowman, Jennifer Grieser, Linda J. Saif, J. Jeffrey Root, Jacqueline M. Nolting, Dusty Lombardi and Devra Huey and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of General Virology.

In The Last Decade

Rachel M. Tell

5 papers receiving 439 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SARS-CoV-2 infection in free-ranging white-tailed deer

2021 231 citations Vanessa L. Hale, Patricia M. Dennis et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rachel M. Tell United States	5	370	185	68	62	52	5	448
Jacob Schön Germany	11	507 1.4×	211 1.1×	60 0.9×	45 0.7×	59 1.1×	21	642
Dashzeveg Bold United States	10	441 1.2×	250 1.4×	40 0.6×	42 0.7×	45 0.9×	19	516
Dillon S. McBride United States	6	229 0.6×	96 0.5×	39 0.6×	72 1.2×	38 0.7×	11	293
François Moutou France	8	281 0.8×	105 0.6×	58 0.9×	69 1.1×	24 0.5×	28	394
Christopher J. Brackman Hong Kong	7	720 1.9×	388 2.1×	54 0.8×	36 0.6×	68 1.3×	14	826
Vibol Hul Cambodia	8	239 0.6×	68 0.4×	84 1.2×	30 0.5×	38 0.7×	18	307
Anna Michelitsch Germany	11	353 1.0×	169 0.9×	105 1.5×	50 0.8×	22 0.4×	14	414
Jingkai Ji China	6	206 0.6×	82 0.4×	48 0.7×	14 0.2×	39 0.8×	13	367
Julianna B. Lenoch United States	7	376 1.0×	128 0.7×	60 0.9×	183 3.0×	32 0.6×	15	506
Danijela Rihtarič Slovenia	8	243 0.7×	119 0.6×	23 0.3×	17 0.3×	19 0.4×	14	311

Countries citing papers authored by Rachel M. Tell

Since Specialization

Citations

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

Fields of papers citing papers by Rachel M. Tell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rachel M. Tell. 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 Rachel M. Tell. The network helps show where Rachel M. Tell may publish in the future.

Co-authorship network of co-authors of Rachel M. Tell

This figure shows the co-authorship network connecting the top 25 collaborators of Rachel M. Tell. A scholar is included among the top collaborators of Rachel M. Tell 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 Rachel M. Tell. Rachel M. Tell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Carpenter, Ann, Ryan M. Wallace, Sarah A. Hamer, et al.. (2023). Clinical and epidemiologic features of SARS-CoV-2 in dogs and cats compiled through national surveillance in the United States. Journal of the American Veterinary Medical Association. 261(4). 480–489. 15 indexed citations

2.

Pelzel‐McCluskey, Angela M., Brad Christensen, John Humphreys, et al.. (2021). Review of Vesicular Stomatitis in the United States with Focus on 2019 and 2020 Outbreaks. Pathogens. 10(8). 993–993. 20 indexed citations

3.

Chandler, Jeffrey C., Sarah N. Bevins, Jeremy W. Ellis, et al.. (2021). SARS-CoV-2 exposure in wild white-tailed deer ( Odocoileus virginianus ). Proceedings of the National Academy of Sciences. 118(47). 162 indexed citations

4.

Hale, Vanessa L., Patricia M. Dennis, Dillon S. McBride, et al.. (2021). SARS-CoV-2 infection in free-ranging white-tailed deer. Nature. 602(7897). 481–486. 231 indexed citations breakdown →

5.

Joshi, Lok R., Danielle Gava, G. F. Kutish, et al.. (2019). Genetic diversity and evolution of the emerging picornavirus Senecavirus A. Journal of General Virology. 101(2). 175–187. 20 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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