Scott Sievert
Impact in
- Agronomy and Crop Science top 2%
- Ruminant Nutrition and Digestive Physiology
- Reproductive Physiology in Livestock
- Forestry top 10%
Papers in
-
- Ruminant Nutrition and Digestive Physiology 4
-
- Machine Learning and Data Classification 3
- Data Stream Mining Techniques 2
- Co-authors
- Randy D. Shaver (4 shared papers)D.K. Combs (1 shared paper)P.C. Hoffman (1 shared paper)Arvind Satyanarayan (1 shared paper)Jake Vanderplas (1 shared paper)Brian Granger (1 shared paper)Dominik Moritz (1 shared paper)Jeffrey Heer (1 shared paper)
- Journals
- Journal of Dairy Science (3 papers)F1000Research (1 paper)Journal of Nonverbal Behavior (1 paper)Journal of Animal Science (1 paper)Affective Science (1 paper)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Scott Sievert
13 papers receiving 693 citations
Peers
Comparison fields: 5 of 125
- Agronomy and Crop Science 251
- Forestry 26
- Environmental Chemistry 49
- Animal Science and Zoology 45
- Genetics 111
Countries citing papers authored by Scott Sievert
This map shows the geographic impact of Scott Sievert'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 Scott Sievert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Sievert more than expected).
Fields of papers citing papers by Scott Sievert
This network shows the impact of papers produced by Scott Sievert. 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 Scott Sievert. The network helps show where Scott Sievert may publish in the future.
Co-authors
The 24 scholars most cited alongside Scott Sievert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 275 | |
| 2 | 1993 | 195 | |
| 3 | 2018 | 150 | |
| 4 | 1993 | 40 | |
| 5 | 1993 | 20 | |
| 6 | 2021 | 16 | |
| 7 | 2019 | 7 | |
| 8 | 2021 | 6 | |
| 9 | 2017 | 6 | |
| 10 | Effects of nonfiber carbohydrate and Aspergillus oryzae fermentation extract on intake, milk production, and digestion in lactating dairy cows. | 1990 | 5 |
| 11 | 2019 | 3 | |
| 12 | 2022 | 2 | |
| 13 | 2022 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2024 | 0 |
About Scott Sievert
Scott Sievert is a scholar working on Agronomy and Crop Science, Artificial Intelligence, Computer Science Applications, Management Science and Operations Research and Experimental and Cognitive Psychology, having authored 15 papers that have together received 727 indexed citations. Recurring topics across this work include Ruminant Nutrition and Digestive Physiology (4 papers), Machine Learning and Data Classification (3 papers), Data Stream Mining Techniques (2 papers), Humor Studies and Applications (2 papers), Advanced Bandit Algorithms Research (2 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Genetic and phenotypic traits in livestock (2 papers) and Neural and Behavioral Psychology Studies (1 paper). The work is most often cited by research in Agronomy and Crop Science (251 citations), Forestry (26 citations), Environmental Chemistry (49 citations), Animal Science and Zoology (45 citations) and Genetics (111 citations). Scott Sievert has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Randy D. Shaver, D.K. Combs, P.C. Hoffman, Arvind Satyanarayan, Jake Vanderplas, Brian Granger, Dominik Moritz, Jeffrey Heer, Kanit Wongsuphasawat and Matthew Rocklin. Their work appears in journals such as Journal of Dairy Science, F1000Research, Journal of Nonverbal Behavior, Journal of Animal Science and Affective Science.
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.