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Record W7083175490 · doi:10.1139/facets-2025-0041

Canada's got your tung? A wealth of opportunity

2025· article· en· W7083175490 on OpenAlexaffvenueabout

Bibliographic record

VenueFACETS · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEastern European Communism and Reforms
Canadian institutionsUniversity of AlbertaUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMesozoicPaleozoicMineralization (soil science)CrustBase metalSkarnSustainable developmentTungstenWolframite

Abstract

fetched live from OpenAlex

Tungsten is an essential metal used in high-heat, high-strength, and high-density applications, making it critical to technologies that support a green and sustainable future. However, global supply is dominated by China, raising concerns about environmental, social, and supply chain risks. Canada, once a significant producer, holds about 20% of the world's tungsten reserves and has the potential to re-emerge as a leading supplier amid rising demand. Tungsten is concentrated in Earth's ancient continental crust and mobilized by tectonic, magmatic, and hydrothermal processes during mountain building. In Canada, most mineralization is linked to two major orogenic events: the Paleozoic Appalachian Orogen in the east and Mesozoic to Cenozoic mountain-building in the Canadian Cordillera. These events produced two principal deposit types, including some of the country's largest resources: granite-hosted veins (e.g., Northern Dancer and Sisson Brook) and skarns (e.g., Cantung and Mactung), among the world's richest. Exploration combines regional methods (e.g., geophysics and mapping) with targeted techniques like till geochemistry and indicator mineral analysis. Despite Canada's strong geological endowment, the remoteness of many deposits remains a barrier. Strategic investment in infrastructure and exploration is essential to unlocking Canada's potential as a sustainable and secure tungsten source.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.318
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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