Arctic supply chain reliability in Baffin Bay and Greenland
Bibliographic record
Abstract
Despite the obvious economic advantages of utilising supply chains across the northern routes, there are significant challenges to their reliability. Every year an increasing number of ships venture into the region to supply, extract or transit the most northern parts of the world. However, supply chain reliability has been a significant challenge for ship operators, despite technological and organisational innovations. This paper investigates the hazards that face Arctic supply chain reliability in the region surrounding Baffin Bay and Greenland as well as the technological and organisational developments that are adopted to mitigate them. A bow-tie approach is used to illustrate the challenges faced by the shipping industry. We conclude that increased traffic will require significant investments in systems and infrastructure developments to manage Arctic hazards, thereby increasing reliability. Specifically, protective barriers like emergency response and icebreaker capacity need to be upgraded and positioned closer to emerging shipping lanes. Northwest Canada and Greenland are both poorly covered in terms of helicopter search and rescue and icebreaker availability. The consequence is that, with the increase in traffic outside the traditional busy routes in the south, supply chains lack access to effective Arctic hazard barriers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".