GoldSpot's proprietary Artificial Intelligence (AI) and geological interpretation highlights lithium potential at Critical Elements' Bourier claims within the Nemiscau greenstone belt
Preliminary Summer 2021 field exploration results have revealed the discovery of five (5) new sectors of spodumene-rich (Li-rich) pegmatites within GoldSpot's targets, highlighting the potential of the Bourier project and the accuracy GoldSpot's targeting
Engagement with Critical Elements to uncover EV battery material showcases GoldSpot's ability to work with leaders across all commodities and deposit types to identify new mineral exploration targets
Toronto, Ontario--(Newsfile Corp. - September 14, 2021) - GoldSpot Discoveries Corp. /zigman2/quotes/210443510/delayed CA:SPOT -1.25% (otcqx:SPOFF) ("GoldSpot" or the "Company"), a leading technology services company leveraging machine learning to transform the mineral discovery process and Critical Elements Lithium Corporation /zigman2/quotes/204783849/delayed CA:CRE +6.34% (otcqx:CRECF) /zigman2/quotes/206100393/delayed DE:F12 +6.60% ("Critical Elements"), are pleased to announce the results of a property-wide comprehensive target generation on Critical Element's Bourier property in the Nemiscau greenstone belt in James Bay, Québec. Critical Elements' Bourier project is under an option agreement by Lomiko Metals .
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. Preliminary Summer 2021 field exploration results from Critical Elements have revealed the discovery of five (5) new sectors of spodumene-rich (Li-rich) pegmatites within GoldSpot's provided targets, highlighting the potential of the Bourier project and the accuracy GoldSpot's Smart Targeting program.
Vincent Dubé-Bourgeois, CEO of GoldSpot Discoveries commented: "GoldSpot's proven A.I. methodology identified prospective Lithium targets on the Bourier project and we are thrilled to announce the results of our investigation and analysis. The new spodumene discoveries within GoldSpot Smart Targets are a great accomplishment for GoldSpot, Critical Elements and Lomiko and we look forward to working to validate additional findings."
Jean-Sébastien Lavallée, CEO of Critical Elements commented: "We are very pleased with the results of the Summer 2021 exploration program conducted on the Bourier project. The surface exploration program has confirmed that combined AI targeting and the outcrop detection conducted by GoldSpot succeeded in identifying new lithium-bearing pegmatites. These tools are extremely useful to reduce exploration cost and time, in particular the large portfolio of 700 square kilometers owned by Critical Elements."
The study hinged on digital extraction from an exhaustive compilation of assessment files, government data and academic studies. This dataset provided outcrop/sample descriptions, bedrock geology, geochemical analyses, and geophysical surveys. Original data was cleaned and combined to create a comprehensive data set for geological interpretation and machine learning processes.
The compilation of discrete outcrop observations allowed a reliable update to existing geologic maps, resulting in a refined, lithium exploration-oriented pegmatite map. A total of 99 pegmatite bodies were added to the current geological map, highlighting previously unknown potential for economic lithium mineralization.
An up-to-date structural interpretation was created based on a high-resolution aeromagnetic survey commissioned by Critical Elements. This survey revealed structurally complex patterns, including large-scale folds and major ENE-trending ductile fault zones.
GoldSpot Lithium Target Generation
GoldSpot generated lithium targets, using a "Smart Targeting" approach of knowledge- and AI data-driven methods.
Processes: The AI data method trained machine learning algorithms to predict the presence of lithium, using all variables (features), both numeric and interpreted on a 10 m x 10 m grid cell datastack. Once the model performs to a satisfactory level, results produced include:
1) a series of zones with relatively high probability of containing lithium;
2) a ranking of feature importance for each input feature.
Performance: The best prediction model for lithium at Bourier was obtained using the Extended Euclidean Algorithm which had a performance metric of 75% precision. The updated geology and structural interpretation were the dominant contributors to the targeting model.
Results: A total of 15 lithium exploration targets were identified (Figure 1), reducing the area of investigation to approximately 9.5% of the total claim holding. The newly interpreted pegmatite outcrops largely controlled the distribution of the lithium targets.
Figure 1: GoldSpot Lithium Targets and location of discoveries of spodumene-rich pegmatite outcrops within Bourier claims.