Gertrude M. Cox

2.1k citations
12 papers · 1.6k indexed · 1 hit paper · h-index 4
Topics
Statistics Education and Methodologies (1 paper)Manufacturing Process and Optimization (1 paper)Additive Manufacturing and 3D Printing Technologies (1 paper)

In The Last Decade

Gertrude M. Cox

12 papers receiving 1.3k citations

Hit Papers

Experimental designs, 2nd ed.195720261980200319574008001.2k

Peers

Gertrude M. Cox
Comparison fields: 5 of 197
  • Plant Science 378
  • Agronomy and Crop Science 249
  • Animal Science and Zoology 155
  • Management Science and Operations Research 155
  • Genetics 145
Replace S. G. Carmer with:
S. G. Carmer United States
Clyde Young Kramer United States
D. A. Preece United Kingdom
R. A. Fox
J. H. Matis United States
Mervyn G. Marasinghe United States
Steven J. Schwager United States
Robert O. Kuehl United States
Derek J. Pike United Kingdom
Walter T. Fédérer United States
Gertrude M. Cox relative to S. G. Carmer United States S. G. Carmer's profile →
Citations per field
00.5×1.5×1.9×
S. G. Carmer · 1×
Citations per year

Countries citing papers authored by Gertrude M. Cox

Since Specialization
Citations

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

Fields of papers citing papers by Gertrude M. Cox

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gertrude M. Cox

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 3
2 3
3 5
4
The Biometric Society, the first twenty-five years (1947-1972).
2
5 2
6 7
7 139
8 3
9 1
10 2
11
Experimental designs, 2nd ed.breakdown →
1465
12 1

About Gertrude M. Cox

Gertrude M. Cox is a scholar working on Statistics and Probability, Industrial and Manufacturing Engineering and Automotive Engineering, having authored 12 papers that have together received 1.6k indexed citations. Recurring topics across this work include Statistics Education and Methodologies (1 paper), Manufacturing Process and Optimization (1 paper) and Additive Manufacturing and 3D Printing Technologies (1 paper). The work is most often cited by research in Agronomy and Crop Science (249 citations), Statistics and Probability (134 citations) and Animal Science and Zoology (155 citations). Gertrude M. Cox has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include William G. Cochran, P.G. Homeyer, Bernard Greenberg, James E. Grizzle, Lyle V. Jones, W. G. Cochran, David Mason, Gordon Simons, Norman L. Johnson and D. S. Villars. Their work appears in journals such as Journal of the American Statistical Association, Physics Today 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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