In from the cold: : How miners and shippers are looking to exploit new Arctic transport routes
Bibliographic record
Abstract
Companies including Denmark-based Greenland Rare Earth Projects and NunaMinerals AS, along with Australian developer Greenland Minerals and Energy Ltd and locally registered Tanbreez Mining AS ( see box ), are hoping to exploit the country's rare earths deposits. Meanwhile UK-headquartered Rare Earth Minerals Plc and Angel Mining Plc are eyeing up its rare earths and zinc resources, respectively, and Canada's Hudson Resources Inc. have an anorthosite project under development. Based in Montreal, it is the country's largest ocean going dry bulk shipping company and its Nunavik bulk carrier was the first vessel to transit Canada's Northwest Passage with an Arctic cargo of nickel concentrate. Its journey started this September and was successfully completed in mid-October, becoming the first vessel to navigate the route unescorted with an Arctic cargo. The use of UAVs is proving to be extremely beneficial to identify many ice features that should be avoided ahead of the vessel, as well as identifying open water leads to improve voyage efficiency, says Thomas Paterson, senior vice-president, ship owning, Arctic and projects, at Fednav. In addition, the deployment of drones fitted with cameras gives the ice navigator another useful aid when making important decisions while transiting heavy ice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".