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

dc.contributor.authorCheng, SH
dc.contributor.authorAugustin, C
dc.contributor.authorBethel, A
dc.contributor.authorGill, D
dc.contributor.authorAnzaroot, S
dc.contributor.authorBrun, J
dc.contributor.authorDeWilde, B
dc.contributor.authorMinnich, RC
dc.contributor.authorGarside, R
dc.contributor.authorMasuda, YJ
dc.contributor.authorMiller, DC
dc.contributor.authorWilkie, D
dc.contributor.authorWongbusarakum, S
dc.contributor.authorMcKinnon, MC
dc.date.accessioned2020-06-22T14:31:24Z
dc.date.issued2018-07-10
dc.description.sponsorshipNational Institute for Health Researchen_GB
dc.description.sponsorshipScience for Nature and People Partnershipen_GB
dc.identifier.citationVol. 32 (4), pp. 762 - 764en_GB
dc.identifier.doi10.1111/cobi.13117
dc.identifier.grantnumberEvidence‐Based Conservation Working Groupen_GB
dc.identifier.urihttp://hdl.handle.net/10871/121588
dc.language.isoenen_GB
dc.publisherWileyen_GB
dc.rights© 2018 Society for Conservation Biology. This is an open access article.en_GB
dc.titleUsing machine learning to advance synthesis and use of conservation and environmental evidenceen_GB
dc.typeArticleen_GB
dc.date.available2020-06-22T14:31:24Z
dc.identifier.issn0888-8892
dc.descriptionThis is the final version. Available from Wiley via the DOI in this record. en_GB
dc.identifier.journalConservation Biologyen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2018-04-03
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2018-04-03
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-06-22T14:27:11Z
refterms.versionFCDVoR
refterms.dateFOA2020-06-22T14:31:29Z
refterms.panelAen_GB


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