How do non-deposit sites influence the performance of machine learning-based gold prospectivity mapping? A study case in the Pitangui Greenstone Belt, Brazil-Reference-Cited by-同舟云学术

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How do non-deposit sites influence the performance of machine learning-based gold prospectivity mapping? A study case in the Pitangui Greenstone Belt, Brazil

Published:2024-09 Issue: Volume:264 Page:107543
ISSN:0375-6742
Container-title:Journal of Geochemical Exploration
language:en
Short-container-title:Journal of Geochemical Exploration

Author:

Ribeiro Brener Otávio Luiz^ORCID,Barbuena Danilo^ORCID,de Melo Gustavo Henrique Coelho^ORCID,Motta João Gabriel^ORCID,Marques Eduardo Duarte^ORCID,de Souza Marinho Marcelo^ORCID

Publisher

Elsevier BV

Reference115 articles.

1. Support vector machine for multi-classification of mineral prospectivity areas;Abedi;Comput. Geosci.,2012

2. Comparações geoquímicas entre os corpos “A” e “C” – Mina de Turmalina (Au), Pitangui (MG);Albuquerque,2019

3. Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran;Almasi;Ore Geology Reviews,2017

4. Genetic implications from textures, mineralogy, and geochemistry: The case of Zona Basal–A singular polymetallic occurrence in the Quadrilátero Ferrífero, Brazil;Alves;Contributions to Mineralogy and Petrology,2022

5. The PB/PB age of the minas supergroup carbonate rocks, quadrilatero FERRIFERO, BRAZIL;Babinski;Precambrian Research,1995

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