Maple Gold Applies Machine Learning for High-Grade Gold Targeting at Douay
Montreal, Quebec--(Newsfile Corp. - July 7, 2020) - Maple Gold Mines Ltd. (TSXV: MGM) (OTCQB: MGMLF) (FSE: M3G) ("Maple Gold" or the "Company") has engaged Computational Geosciences Inc. ("CGI") to complete a new and expanded Artificial Intelligence ("AI") study for targeting high-grade gold at Douay. This study will use all available digital datasets within a 128km² area centered on the resource area (Fig. 1) in order to generate gold prospectivity maps and provide additional target areas to validate and rank in advance of the Company's next phase of drilling later this year.
AI studies, as applied to Mineral Exploration, involve the application of automated mathematical models (intelligent algorithms) to data-rich environments in order to allow recognition of subtle features or patterns in the data that are not always evident to the human eye. CGI will be employing their proprietary VNet segmentation deep learning algorithm to help the Company's targeting efforts.
The Company believes that the quality of its databases, together with CGI's rigorous methodology and built-in interaction with the Company's geologists at all stages of the process, will result in a high quality product that will allow for the definition of additional new drill targets.
Maple Gold's President and CEO, Matthew Hornor, commented: "Our team is excited to collaborate with CGI, a group we are very familiar with given their strategic partnerships with the Ivanhoe group of companies. The last time any machine learning was applied at Douay was limited and more than a decade ago. There is significantly more project data now, with more sophisticated algorithms and increased computing power on the processing side. We are excited to complete this exercise in parallel with our IP program as we refine and detail top priority discovery targets in advance of our planned drilling in late Q3 or early Q4."
VNet is a customized convolutional neural network (CNN) that can handle an arbitrary number of geoscience data inputs in either 2D or 3D. This customized CNN is sensitive to sparse or dense data areas, can detect multiple feature resolutions (i.e. regional trends vs. local anomalies) and is scalable across large areas. This style of deep learning for mineral exploration is an emerging technology that requires expertise in geoscience data processing, data interpretation and artificial intelligence. The biggest advantage of a data-driven solution is to extract subtle correlations across multiple datasets over a large spatial area, all while reducing human bias. By generating targets with deep learning, and vetting them with an experienced geoscience team, the expertise of the human is still utilized but complemented by the power of the machine.
To view an enhanced version of Figure 1, please visit:
CGI's methodology includes a multi-step process that will involve close interaction between CGI and Maple Gold geologists. The database review and validation step has largely been completed, with the next step being the generation of preliminary prospectivity maps. Final results, prospectivity maps and a corresponding report are expected in Q3.
About Maple Gold
Maple Gold is an advanced gold exploration and development company focused on defining a district-scale gold project in one of the world's premier mining jurisdictions. The Company's ~355 km² Douay Gold Project is located along the Casa Berardi Deformation Zone (55 km of strike) within the prolific Abitibi Greenstone Belt in northern Quebec, Canada. The Project benefits from excellent infrastructure and has an established gold resource that remains open in multiple directions. For more information please visit www.maplegoldmines.com.
Computational Geosciences Inc. is a world leading consulting company in artificial intelligence and geophysical 3D inversion modelling. Our strength is the combination of geoscience data expertise within the natural resource sector, coupled with innovative inversion and machine learning capabilities. By leveraging these knowledge bases within our customized convolutional neural network architecture (VNET), CGI applies a novel approach to prospectivity mapping in order to find the discoveries of tomorrow.
The scientific and technical data contained in this press release was reviewed and prepared under the supervision of Fred Speidel, M. Sc., P. Geo., Vice-President Exploration, of Maple Gold. Mr. Speidel is a Qualified Person under National Instrument 43-101 Standards of Disclosure for Mineral Projects. Mr. Speidel has verified the data related to the exploration information disclosed in this news release through his direct participation in the work. For a complete description of protocols, please visit the Company's QA/QC page on the website at: http://maplegoldmines.com/index.php/e n/projects/qa-qc-qp-statement.
ON BEHALF OF MAPLE GOLD MINES LTD.
B. Matthew Hornor, President & CEO
For Further Information Please Contact:
Mr. Joness Lang
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Forward Looking Statements:
This news release contains "forward-looking information" and "forward-looking statements" (collectively referred to as "forward-looking statements") within the meaning of applicable Canadian securities legislation in Canada, including statements about the prospective mineral potential of the Porphyry Zone, the potential for significant mineralization from other drilling in the referenced drill program and the completion of the drill program. Forward-looking statements are based on assumptions, uncertainties and management's best estimate of future events. Actual events or results could differ materially from the Company's expectations and projections. Investors are cautioned that forward-looking statements involve risks and uncertainties. Accordingly, readers should not place undue reliance on forward-looking statements. Forward-looking statements include, but are not limited to, statements regarding timing and completion of the private placement. When used herein, words such as "anticipate", "will", "intend" and similar expressions are intended to identify forward-looking statements.
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