Scarlett Bailey

8 total papers · 554 total citations
4 papers, 429 citations indexed

About

Scarlett Bailey is a scholar working on Artificial Intelligence, Environmental Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Scarlett Bailey has authored 4 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Environmental Engineering and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Scarlett Bailey's work include Soil Geostatistics and Mapping (3 papers), Geochemistry and Geologic Mapping (3 papers) and Mineral Processing and Grinding (1 paper). Scarlett Bailey is often cited by papers focused on Soil Geostatistics and Mapping (3 papers), Geochemistry and Geologic Mapping (3 papers) and Mineral Processing and Grinding (1 paper). Scarlett Bailey collaborates with scholars based in United States, Australia and China. Scarlett Bailey's co-authors include Richard Ferguson, Wartini Ng, Alex B. McBratney, Budiman Minasny, Maryam Montazerolghaem, José Padarian, C. A. Seybold, Skye Wills, J. P. Anderson and P. A. Thomas and has published in prestigious journals such as PLoS ONE, Soil Science Society of America Journal and Geoderma.

In The Last Decade

Scarlett Bailey

4 papers receiving 422 citations

Hit Papers

Convolutional neural netw... 2019 2026 2021 2023 2019 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Scarlett Bailey 254 192 163 68 67 4 429
Alexia Gobrecht 235 0.9× 162 0.8× 135 0.8× 50 0.7× 91 1.4× 14 412
Georgios Tziotzios 222 0.9× 166 0.9× 124 0.8× 50 0.7× 95 1.4× 7 411
Antonios Morellos 223 0.9× 165 0.9× 124 0.8× 49 0.7× 103 1.5× 6 428
André Marcelo de Souza 144 0.6× 193 1.0× 91 0.6× 34 0.5× 29 0.4× 14 370
Michel Rabenarivo 191 0.8× 131 0.7× 98 0.6× 130 1.9× 87 1.3× 15 422
Ruili Shen 238 0.9× 158 0.8× 238 1.5× 23 0.3× 63 0.9× 9 389
Wanzhu Ma 152 0.6× 79 0.4× 77 0.5× 142 2.1× 88 1.3× 12 404
Gao Yin 162 0.6× 200 1.0× 199 1.2× 11 0.2× 118 1.8× 16 412
J.O. Sickman 337 1.3× 147 0.8× 217 1.3× 123 1.8× 90 1.3× 7 430
Larry L. Freeborn 146 0.6× 61 0.3× 72 0.4× 182 2.7× 53 0.8× 9 369

Countries citing papers authored by Scarlett Bailey

Since Specialization
Citations

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

Fields of papers citing papers by Scarlett Bailey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Scarlett Bailey

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

All Works

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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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