Can the Arctic be a significant contributor of critical minerals for the global energy transition?
Bibliographic record
Abstract
The demand for critical minerals is rising in support of the low-carbon energy transition, as well as global economic growth. Despite its hostile environment, the Arctic is a region with historic and existing mineral production. This paper assesses the potential of the Arctic to make a significant contribution to the future supply of critical minerals. It is one of the first, possibly the first, attempt to do so at a pan-Arctic scale and with a focus on critical minerals for the energy transition. Even though the mineral geology of the Arctic is not special, various physical and human geographic factors mean that the costs and timelines for mineral extraction from the Arctic are significantly greater than that for many other parts of the world. Given the scale of the Arctic's current mining operations and the need to boost mineral production and exports, it is possible that the major growth of production between now and 2034 will be in Russia. The period beyond the mid-2030s is when the Arctic regions could possibly start to provide a greater share of global supplies of critical minerals. The speed at which this takes place will depend on factors such as the rate of growth of demand for different critical minerals, the economic competitiveness of critical mineral supplies from Arctic regions compared with those from the rest of the world, and the scale of government and societal support. The exact locations of the mines will vary between minerals, but Russia and Canada are likely to feature strongly for several minerals on account of their geographic size. Other countries may become regionally important suppliers for specific minerals, for example Greenland and Sweden for rare earths. Sub-sea exploitation is likely to have started as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".