Using machine learning to advance synthesis and use of conservation and environmental evidence

Article impact statement: Machine learning optimizes processes of systematic evidence synthesis and improves its utility for evidence‐based conservation.

Bibliographic Details

Published in:	Conservation biology Vol. 32; no. 4; pp. 762 - 764
Main Authors:	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.
Format:	Journal Article
Language:	English
Published:	United States Wiley Blackwell, Inc 01-08-2018 Blackwell Publishing Ltd
Subjects:	Artificial intelligence Conservation Environmental impact Learning algorithms Letter Machine learning Synthesis
Online Access:	Get full text
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