Bridget Wasser

886 total citations · 1 hit paper
8 papers, 637 citations indexed

About

Bridget Wasser is a scholar working on Animal Science and Zoology, Food Science and Small Animals. According to data from OpenAlex, Bridget Wasser has authored 8 papers receiving a total of 637 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Animal Science and Zoology, 4 papers in Food Science and 3 papers in Small Animals. Recurrent topics in Bridget Wasser's work include Meat and Animal Product Quality (8 papers), Animal Nutrition and Physiology (4 papers) and Sensory Analysis and Statistical Methods (4 papers). Bridget Wasser is often cited by papers focused on Meat and Animal Product Quality (8 papers), Animal Nutrition and Physiology (4 papers) and Sensory Analysis and Statistical Methods (4 papers). Bridget Wasser collaborates with scholars based in United States. Bridget Wasser's co-authors include Chris R. Calkins, L. S. PAPADOPOULOS, D. A. King, Mark F. Miller, K. E. Belk, Michael E. Dikeman, Dustin T Yates, T. L. Wheeler, Todd K. Shackelford and R. K. Miller and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Animal Science and Meat Science.

In The Last Decade

Bridget Wasser

8 papers receiving 622 citations

Hit Papers

Research Guidelines for Cookery, Sensory Evaluation, and ... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bridget Wasser United States 7 596 196 95 73 69 8 637
Ceferina Vieira Spain 15 675 1.1× 197 1.0× 117 1.2× 71 1.0× 92 1.3× 36 778
E. Muela Spain 16 653 1.1× 241 1.2× 92 1.0× 62 0.8× 69 1.0× 24 740
José A. Silva Portugal 14 547 0.9× 196 1.0× 72 0.8× 47 0.6× 60 0.9× 41 771
R. J. Maddock United States 18 817 1.4× 230 1.2× 151 1.6× 106 1.5× 78 1.1× 40 953
W. R. Caine Canada 16 587 1.0× 195 1.0× 107 1.1× 121 1.7× 37 0.5× 30 775
M. Pérez-Juan Spain 17 604 1.0× 228 1.2× 49 0.5× 87 1.2× 64 0.9× 23 774
M.V. Sarriés Spain 16 695 1.2× 271 1.4× 84 0.9× 121 1.7× 77 1.1× 35 808
I. L. Larsen Canada 16 546 0.9× 139 0.7× 42 0.4× 51 0.7× 46 0.7× 57 640
L. S. PAPADOPOULOS United States 7 648 1.1× 253 1.3× 93 1.0× 87 1.2× 62 0.9× 10 723
D.R. McKenna United States 14 977 1.6× 273 1.4× 77 0.8× 85 1.2× 98 1.4× 32 1.1k

Countries citing papers authored by Bridget Wasser

Since Specialization
Citations

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

Fields of papers citing papers by Bridget Wasser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bridget Wasser

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

All Works

8 of 8 papers shown
1.
Miller, R. K., et al.. (2023). Prediction of beef tenderness and juiciness using consumer and descriptive sensory attributes. Meat Science. 205. 109292–109292. 10 indexed citations
2.
Arnold, A. N., J. Chance Brooks, Chad Carr, et al.. (2017). National Beef Tenderness Survey—2015: Palatability and Shear Force Assessments of Retail and Foodservice Beef. SHILAP Revista de lepidopterología. 1(1). 49 indexed citations
3.
Arnold, A. N., R. K. Miller, Kerri B. Gehring, et al.. (2015). Tenderness assessments of top loin steaks from retail markets in four U.S. cities1. Journal of Animal Science. 93(10). 4610–4616. 8 indexed citations
4.
Wheeler, T. L., L. S. PAPADOPOULOS, K. E. Belk, et al.. (2015). Research Guidelines for Cookery, Sensory Evaluation, and Instrumental Tenderness Measurements of Meat. 463 indexed citations breakdown →
5.
Brooks, J.C., Christopher Alfred Carr, R. J. Delmore, et al.. (2012). National Beef Tenderness Survey–2010: Warner-Bratzler shear force values and sensory panel ratings for beef steaks from United States retail and food service establishments1. Journal of Animal Science. 91(2). 1005–1014. 65 indexed citations
6.
West, Sarah E., K.L. Nicholson, Joel D. Nicholson, et al.. (2011). Innovative retail merchandising strategies to accommodate for the growing trend of heavier carcass weights in the United States. Meat Science. 88(4). 610–618. 4 indexed citations
7.
Lorenzen, C. L., et al.. (2010). Efficacy of performing Warner–Bratzler and slice shear force on the same beef steak following rapid cooking. Meat Science. 85(4). 792–794. 30 indexed citations
8.
Nicholson, K.L., J.C. Brooks, R. J. Delmore, et al.. (2008). National Beef Market Basket Survey – 2006: External fat thickness measurements and separable component determinations for beef from US retail establishments. Meat Science. 81(2). 335–343. 8 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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