Data-driven gold potential maps for the Chibougamau area, Abitibi greenstone belt, Canada.

The first image is a Mineral Prospectivity Map (MPM) produced using 35 input predictor variables (maps) and the Random Forest (RF) machine learning algorithm whereas the second image is the same except it was produced using the best 10 predictor variables calculated by the RF algorithm. [Display omitted] • Mineral prospectivity mapping (MPM) • Geology – Chibougamau, Quebec. • Gold (Au) model. Two mineral prospectivity maps (MPM) focusing on a general Au model for the Chibougamau region of Quebec, Canada, have been produced in this paper. The random forest algorithm has been used to integrate 35 evidence (predictor) layers which represent vectors to Au mineralization. The MPMs generated are robust as evidenced by efficiency of classification curves. The known zones of Au mineralization are well predicted; furthermore, new prospective areas with no known Au have been identified which are prime for exploration follow-up. The Chibougamau area is somewhat fertile with respect to Au and the strongest predictors are fault density and intersection density, contact density and Au anomalies in rock. [ABSTRACT FROM AUTHOR]