Silva dos Santos, V.; Gloaguen, E.; Hector Abud Louro, V.; Blouin, M.
Machine Learning Methods for Quantifying Uncertainty in Prospectivity Mapping of Magmatic-Hydrothermal Gold Deposits: A Case Study from Juruena Mineral Province, Northern Mato Grosso, Brazil. Minerals 2022, 12, 941.
https://doi.org/10.3390/min12080941
AMA Style
Silva dos Santos V, Gloaguen E, Hector Abud Louro V, Blouin M.
Machine Learning Methods for Quantifying Uncertainty in Prospectivity Mapping of Magmatic-Hydrothermal Gold Deposits: A Case Study from Juruena Mineral Province, Northern Mato Grosso, Brazil. Minerals. 2022; 12(8):941.
https://doi.org/10.3390/min12080941
Chicago/Turabian Style
Silva dos Santos, Victor, Erwan Gloaguen, Vinicius Hector Abud Louro, and Martin Blouin.
2022. "Machine Learning Methods for Quantifying Uncertainty in Prospectivity Mapping of Magmatic-Hydrothermal Gold Deposits: A Case Study from Juruena Mineral Province, Northern Mato Grosso, Brazil" Minerals 12, no. 8: 941.
https://doi.org/10.3390/min12080941
APA Style
Silva dos Santos, V., Gloaguen, E., Hector Abud Louro, V., & Blouin, M.
(2022). Machine Learning Methods for Quantifying Uncertainty in Prospectivity Mapping of Magmatic-Hydrothermal Gold Deposits: A Case Study from Juruena Mineral Province, Northern Mato Grosso, Brazil. Minerals, 12(8), 941.
https://doi.org/10.3390/min12080941