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Vector representations of the Canadian Geoscience Foundation model / M. Parsa.M183-2/9318E-PDF

"The Geological Survey of Canada (GSC) has recently developed several data-driven, geospatial predictive models, with more expected to follow. Nevertheless, several challenges hinder the advancement of this initiative. First, the geoscientific phenomena, such as mineralization, targeted by geospatial predictive modelling tasks are typically rare events, which limits the effectiveness of conventional data-driven algorithms. Second, training models from scratch for each task is both resource-intensive and time-consuming. The Canadian Geoscience Foundation model (CGF) offers a promising solution to the aforementioned challenges by providing a general-purpose, adaptable AI model trained on extensive, diverse, pan-Canadian geoscientific datasets"--Page 1.

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.957831&sl=0

Publication information
Department/Agency
  • Geological Survey of Canada, issuing body.
TitleVector representations of the Canadian Geoscience Foundation model / M. Parsa.
Series title
  • Open file, 2816-7155 ; 9318e
Publication typeMonograph - View Master Record
Language[English]
Other language editions[French]
FormatDigital text
Electronic document
Note(s)
  • Issued also in French under title: Représentations vectorielles du modèle fondateur géoscientifique canadien.
  • Includes bibliographical references (page 5).
Publishing information
  • [Ottawa] : Geological Survey of Canada, 2025.
  • ©2025
Author / Contributor
  • Parsa, M., author.
Description1 online resource (5 pages).
ISBN9780660799858
Catalogue number
  • M183-2/9318E-PDF
Subject terms
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