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Using machine learning to advance synthesis and use of conservation and environmental evidence
Resource type
Journal Article
Authors/contributors
- Cheng, Samantha H. (Author)
- Augustin, Caitlin (Author)
- Bethel, Alison (Author)
- Gill, David (Author)
- Anzaroot, Sam (Author)
- Brun, J (Author)
- DeWilde, B. (Author)
- Minnich, R. C. (Author)
- Garside, Ruth (Author)
- Masuda, Yuta J. (Author)
- Miller, Daniel C. (Author)
- Wilkie, David (Author)
- Wongbusarakum, Supin (Author)
- McKinnon, Madeleine C. (Author)
Title
Using machine learning to advance synthesis and use of conservation and environmental evidence
Abstract
Article impact statement : Machine learning optimizes processes of systematic evidence synthesis and improves its utility for evidence‐based conservation.
Publication
Conservation Biology
Volume
32
Issue
4
Pages
762-764
Date
2018-07-10
ISSN
0888-8892
Call Number
openalex: W2797780449
Extra
openalex: W2797780449
mag: 2797780449
Citation
Cheng, S. H., Augustin, C., Bethel, A., Gill, D., Anzaroot, S., Brun, J., DeWilde, B., Minnich, R. C., Garside, R., Masuda, Y. J., Miller, D. C., Wilkie, D., Wongbusarakum, S., & McKinnon, M. C. (2018). Using machine learning to advance synthesis and use of conservation and environmental evidence. Conservation Biology, 32(4), 762–764. https://doi.org/10.1111/cobi.13117
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