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231225s2019 xx |||||o 00| ||eng c |
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7 |
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|a 10.1111/cobi.13104
|2 doi
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|a eng
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| 100 |
1 |
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|a Di Minin, Enrico
|e verfasserin
|4 aut
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| 245 |
1 |
2 |
|a A framework for investigating illegal wildlife trade on social media with machine learning
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| 264 |
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1 |
|c 2019
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Completed 17.10.2019
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|a Date Revised 25.07.2020
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| 500 |
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a © 2018 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.
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| 520 |
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|a Article impact statement: Machine learning can be used to automatically monitor and assess illegal wildlife trade on social media platforms
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| 650 |
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|a Journal Article
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| 650 |
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4 |
|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Fink, Christoph
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Hiippala, Tuomo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Tenkanen, Henrikki
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Conservation biology : the journal of the Society for Conservation Biology
|d 1999
|g 33(2019), 1 vom: 05. Feb., Seite 210-213
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|x 1523-1739
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|g volume:33
|g year:2019
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|g day:05
|g month:02
|g pages:210-213
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