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...

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Bibliographic Details
Main Authors: Jukka-Pekka Ranta, Nick Cook, Sabine Gilbricht
Format: Article
Language:English
Published: Geological Society of Finland 2021-12-01
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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