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Trace element composition of chalcopyrite as a tool for deposit type discrimination from magmatic and hydrothermal settings: a machine learning approach

Crossref DOI link: https://doi.org/10.1007/s00126-025-01388-2

Published Online: 2025-09-02

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Caraballo, Enzo

Beaudoin, Georges

Dare, Sarah
Funding

Funding for this research was provided by:

NSERC, Agnico Eagle Mines ltd., Ministère de l’Énergie et des Ressources Naturelles du Québec
License Information

Text and Data Mining valid from 2025-09-02

Version of Record valid from 2025-09-02
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Article History

Received: 10 September 2024

Accepted: 11 August 2025

First Online: 2 September 2025

Declarations

:

: The research was funded by Agnico Eagle Mines Ltd., the Ministère de l’Énergie et des Ressources Naturelles du Québec and the Natural Sciences and Engineering Research Council.

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