GoldSpot Targeting Results in a High-Grade Gold Discovery at Pretium Resources' Golden Marmot Zone
Toronto, October 27, 2021 - GoldSpot Discoveries Corp. (TSXV: SPOT) (OTCQX: SPOFF) ("GoldSpot" or the "Company"), a leading technology services company leveraging machine learning to transform the mineral discovery process, and Pretium Resources Inc. (TSX: PVG) (NYSE: PVG) ("Pretium"), are pleased to announce the results of the first phase of prospectivity analysis on the Brucejack Property in Northern British Columbia. Integrated geoscience interpretations, including geochemistry, geophysics, and hyperspectral remote sensing were underpinned by GoldSpot's machine learning algorithms to identify 65 targets around the Brucejack mine, with Golden Marmot ranking as a high-priority drill target for quartz-vein-hosted gold mineralization.
Figure 1: Prospectivity results for epithermal style mineralization. The Golden Marmot zone is approximately 3km to the NW of the Brucejack infrastructure
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GoldSpot works with leading exploration and mining clients across all commodities and deposit types, using cutting-edge technology and geoscientific expertise to mitigate exploration risks and significantly increase the efficiency and success rate of mineral exploration across resources. Assay results have been received from the first nine holes of drilling, eight of which intersected gold mineralization (see Pretium news release dated October 25, 2021) at the Golden Marmot Zone, which was highlighted as a high priority target by GoldSpot's geodatascience team.
"The results from Pretium's high-grade gold discovery are incredible and showcase the power of GoldSpot's innovative approach, combining traditional targeting and machine learning to identify high-priority targets," said Denis Laviolette, Executive Chairman and President of GoldSpot. "We look forward to advancing our work with Pretium to expand the potential of the Brucejack Property."
The targets were identified using an innovative integrated approach, combining traditional targeting and machine learning. The traditional geoscience targeting included structural analysis from geophysics, multivariate analysis from geochemistry, and dimension reduction processing of hyperspectral images; derivative products created during the traditional interpretation were used as input variables for the supervised machine learning workflow, which was undertaken using a series of carefully curated training points. Prospectivity scores were generated for four distinct mineralization styles (epithermal, porphyry Au, Au-quartz veins, and polymetallic veins).
A second phase of the prospectivity analysis, encompassing the entire Bowser property, was completed in August 2021.
The technical information in this press release has been prepared in accordance with the Canadian regulatory requirements set out in National Instrument 43-101, Standards of Disclosure for Mineral Projects, and reviewed and approved by Chris MacInnis, professional geoscientist (APGO No. 2059), a qualified person as defined by NI 43-101 guidelines.
About GoldSpot Discoveries Corp.
GoldSpot Discoveries Corp. (TSXV: SPOT) (OTCQX: SPOFF) is a technology company using artificial intelligence to revolutionize the future of global mineral exploration with a full suite of data and knowledge-driven SaaS tools and services. GoldSpot works with industry leaders across all commodity and deposit types to identify new exploration targets, develop cutting-edge technologies and to strategically invest in mineral exploration companies. Our leading team of expert scientist's merge geoscience and data science to deliver bespoke solutions that save time, reduce costs and produce far more accurate results than ever before possible.
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Executive Chairman and President
GoldSpot Discoveries Corp.
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