{'fraction_non_alphanumeric': 0.025296442687747035, 'fraction_numerical': 0.0015810276679841897, 'mean_word_length': 4.702702702702703, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Optimizing cut-off grade considering grade estimation uncertainty - A case study of Witwatersrand gold-producing areas

Due to grade estimation uncertainty, two statistical errors can occur. The Type I error is where material is classified as ore and mined, despite the true value being below the break-even grade. This material is dilution. The Type II error is where the material is estimated to be below the cut-off grade and is classified as waste, although the true grade is actually above the break-even grade. This material is not mined and is lost. The uncertainty was assumed to follow a normal distribution in a previous study. For this study, estimated block values are compared to those determined after mining (the best estimate of the true grade). This actual data from four mines shows that the uncertainty follows a Laplace distribution. There is no single solution regarding adjusting the cut-off grade away from the break-even grade, considering estimation uncertainty, that could be applied to all gold mines. However, adjusting the cut-off grade downwards (up to 22% for one mine) is noted when optimizing the profit considering grade uncertainties. This type of adjustment could open up significant mining areas and extend the life of the mine.