Data for: Quantify continental crustal thickness using the machine learning method

Published: 14 June 2022| Version 1 | DOI: 10.17632/2x62n2dgds.1
Contributor:
Peng Guo

Description

Table S1 The compositions and corresponding crustal thickness of the training data Table S2 The compositions and predicted crustal thickness of the magmatic rocks in the Gangdese Belt in southern Tibet Table S3 The compositions and predicted crustal thickness of the Mesozoic magmatic rocks in the Erguna Block Table S4 The porphyry copper deposits in the Erguna Block

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Geochemistry, Machine Learning

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