SEM-based automated mineralogy (SEM-AM) and unsupervised machine learning studying the textural setting and elemental association of gold in the Rajapalot Au-Co area, northern Finland
SEM-based automated mineralogy (SEM-AM) techniques allow fast and effective way of studying the textural settings of gold in hydrothermal deposits. Unsupervised machine learning (e.g. self-organizing maps) is an intuitive way of processing multi-dimensional geochemical datasets in order to reveal...
Main Authors: | Jukka-Pekka Ranta, Nick Cook, Sabine Gilbricht |
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Format: | Article |
Language: | English |
Published: |
Geological Society of Finland
2021-12-01
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Series: | Bulletin of the Geological Society of Finland |
Subjects: | |
Online Access: | https://www.geologinenseura.fi/sites/geologinenseura.fi/files/bulletin_vol93_2_129-154_ranta-etal.pdf |
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