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A Review of Orebody Knowledge Enhancement Using Machine Learning on Open-Pit Mine Measure-While-Drilling Data.
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- Machine Learning & Knowledge Extraction, 2024, v. 6, n. 2, p. 1343, doi. 10.3390/make6020063
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- Article
Geologist in the Loop: A Hybrid Intelligence Model for Identifying Geological Boundaries from Augmented Ground Penetrating Radar.
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- Geosciences (2076-3263), 2021, v. 11, n. 7, p. 284, doi. 10.3390/geosciences11070284
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- Article
Importance of representative metallurgical sampling and testwork programmes to reduce project risk – a gold case study.
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- Mining Technology (2572-6668), 2019, v. 128, n. 4, p. 230, doi. 10.1080/25726668.2019.1628462
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- Article
Integrating the Theory of Sampling into Underground Mine Grade Control Strategies: Case Studies from Gold Operations.
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- Minerals (2075-163X), 2019, v. 9, n. 4, p. 238, doi. 10.3390/min9040238
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- Article
Geometallurgy—A Route to More Resilient Mine Operations.
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- Minerals (2075-163X), 2018, v. 8, n. 12, p. 560, doi. 10.3390/min8120560
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- Article
Geometallurgical Study of a Gravity Recoverable Gold Orebody.
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- Minerals (2075-163X), 2018, v. 8, n. 5, p. 186, doi. 10.3390/min8050186
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- Article
Integrating the Theory of Sampling into Underground Mine Grade Control Strategies.
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- Minerals (2075-163X), 2018, v. 8, n. 6, p. 232, doi. 10.3390/min8060232
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- Publication type:
- Article
Towards Representative Metallurgical Sampling and Gold Recovery Testwork Programmes.
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- Minerals (2075-163X), 2018, v. 8, n. 5, p. 193, doi. 10.3390/min8050193
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- Article