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

Charles L. Bérubé, Gema R. Olivo, Michel C. Chouteau, Stéphane Perrouty, Pejman Shamsipour, Randolph J. Enkin, William A. Morris, Leonardo Feltrin and Raphaël Thiémonge

Article (2018)

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Department:	Department of Civil, Geological and Mining Engineering
PolyPublie URL:	https://publications.polymtl.ca/39577/
Journal Title:	Ore Geology Reviews (vol. 96)
Publisher:	Elsevier
DOI:	10.1016/j.oregeorev.2018.04.011
Official URL:	https://doi.org/10.1016/j.oregeorev.2018.04.011
Date Deposited:	18 Apr 2023 15:02
Last Modified:	08 Apr 2025 07:03

Cite in APA 7:

Bérubé, C. L., Olivo, G. R., Chouteau, M. C., Perrouty, S., Shamsipour, P., Enkin, R. J., Morris, W. A., Feltrin, L., & Thiémonge, R. (2018). 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. Ore Geology Reviews, 96, 130-145. https://doi.org/10.1016/j.oregeorev.2018.04.011

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