Element-to-mineral-properties conversion (EMPC) via MARSpline for 3D geometallurgical modeling of the Koashva Apatite-Nepheline Deposit, Kola Peninsula, Russia

Abstract Efficient processing of complex ores is often hampered by an incomplete understanding of the spatial distribution of critical mineralogical properties. Here, we introduce a machine learning-based framework that addresses this gap. Using the multivariate adaptive regression splines (MARSplin...

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Autores principales:	A. O. Kalashnikov, A. S. Ganyushkina, G. O. Nagovitsyn, N. G. Konopleva
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Nature Portfolio 2026-05-01
Colección:	Scientific Reports
Materias:	Mineral deposit modelling Machine learning Geometallurgy Kola Alkaline Province Khibiny Apatite
Acceso en línea:	https://doi.org/10.1038/s41598-026-52558-9
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