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Predicting rock type and detecting hydrothermal alteration using machine learning and petrophysical properties of the Canadian Malartic ore and host rocks, Pontiac Subprovince, Québec, Canada

Article ID Journal Published Year Pages File Type
8909527 Ore Geology Reviews 2018 16 Pages PDF
Keywords
Intrusion-related gold depositsMineral explorationPetrophysical propertiesSupport vector machinesSupervised machine learning
Related Topics
Physical Sciences and Engineering Earth and Planetary Sciences Economic Geology
Preview
Predicting rock type and detecting hydrothermal alteration using machine learning and petrophysical properties of the Canadian Malartic ore and host rocks, Pontiac Subprovince, Québec, Canada
Authors
Charles L. Bérubé, Gema R. Olivo, Michel Chouteau, Stéphane Perrouty, Pejman Shamsipour, Randolph J. Enkin, William A. Morris, Leonardo Feltrin, Raphaël Thiémonge,
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Journal
Ore Geology Reviews
Journal: Ore Geology Reviews
Related Categories
Intrusion-related gold deposits
Mineral exploration
Petrophysical properties
Support vector machines
Supervised machine learning
Atmospheric Science
Computers in Earth Sciences
Earth and Planetary Sciences (General)
Earth-Surface Processes
Economic Geology
Geochemistry and Petrology
Geology
Geophysics
Geotechnical Engineering and Engineering Geology
Oceanography
Palaeontology
Space and Planetary Science
Stratigraphy
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