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Machine Learning Investigation of Clinopyroxene Compositions to Evaluate and Predict Mantle Metasomatism Worldwide.

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Title: Machine Learning Investigation of Clinopyroxene Compositions to Evaluate and Predict Mantle Metasomatism Worldwide.
Authors: Qin, Ben1,2 (AUTHOR) charlesbenq@zju.edu.cn, Huang, Fang3 (AUTHOR), Huang, Shichun4 (AUTHOR), Python, Andre5 (AUTHOR), Chen, Yunfeng1,2 (AUTHOR), ZhangZhou, J1,2 (AUTHOR) zhangzhou333@zju.edu.cn
Source: Journal of Geophysical Research. Solid Earth. May2022, Vol. 127 Issue 5, p1-15. 15p.
Database: Environment Complete
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An: 157111926
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PubType: Academic Journal
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  Data: Machine Learning Investigation of Clinopyroxene Compositions to Evaluate and Predict Mantle Metasomatism Worldwide.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Geophysical+Research%2E+Solid+Earth%22">Journal of Geophysical Research. Solid Earth</searchLink>. May2022, Vol. 127 Issue 5, p1-15. 15p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=157111926
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      – Type: doi
        Value: 10.1029/2021JB023614
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 1
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      – TitleFull: Machine Learning Investigation of Clinopyroxene Compositions to Evaluate and Predict Mantle Metasomatism Worldwide.
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            NameFull: Chen, Yunfeng
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            – D: 01
              M: 05
              Text: May2022
              Type: published
              Y: 2022
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