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Abstract Details

(2020) Compositional Evolution of Cretaceous Cordilleran Volcanism

Allen S, Lee C-T & Minisini D

https://doi.org/10.46427/gold2020.39

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05d: Room 2, Friday 26th June 22:24 - 22:27

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Submitted by UQAC Mathieu on Thursday 25th June 23:05
Many thanks for a great presentation. It is also possible to model pre-alteration major element composition (not just SiO2) using a neural network-derived method - I donno if this could apply to your dataset, would be happy to discuss it if you wish (Trépanier, S., Mathieu, L., Daigneault, R., & Faure, S. (2016). Precursors predicted by artificial neural networks for mass balance calculations: Quantifying hydrothermal alteration in volcanic rocks. Computers & Geosciences, 89, 32-43.)
Thank you for this idea - it is definitely both interesting and relevant to my work! My samples are quite altered, and I’ve been concerned about some slight mobility in elements such as Y and Al, which is why I’ve focused so far on Ti and Zr, which both appear immobile. It would be interesting to go back and look at my data for the other elements employed in this method to determine which of my samples I may be able to apply this procedure to. I’m excited to look into this further – thanks!

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