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Using machine learning to advance synthesis and use of conservation and environmental evidence
Author(s) -
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.,
McKin M.C.
Publication year - 2018
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/cobi.13117
Subject(s) - computer science , environmental planning , artificial intelligence , geography
Article impact statement : Machine learning optimizes processes of systematic evidence synthesis and improves its utility for evidence‐based conservation.