Relevance and potential of the Arctic Sea Routes on the LNG trade
Bibliographic record
Abstract
The retreat of the ice around the freezing waters of the Arctic Ocean is opening new waterways where shipping activity could transport commodities between continents. One of the essential products is natural gas - LNG, which is transported in large tankers from exporters to importers. This study aims to explore the dynamics of the LNG trade by using these new tentative routes with conventional sea lanes and estimating the changes in the LNG trade. We utilize Agent-Based Modeling to develop a global LNG model with interactive GIS features, where the agents are the players in the LNG market. The results demonstrate the preponderance of the North-East Passage (NEP, Eurasian Arctic waters) over the North-Western Passage (NWP, the Canadian Arctic) in providing a shortcut connecting Europe with Asia. This passage favors a growing exporter like Russia with exporting facilities in Siberia and future strategic projects to increase liquefaction capacity. The NEP becomes crucial when considering scenarios of a European ban on Russian imports, as European countries are planning due to the crisis with Russia. On the importing side, the Asian Pacific and South Asian importers are the winners with a diverse and shorter LNG supply source. Future Canadian projects may also benefit from these new highways. However, there are also substantial challenges to providing the NEP with the proper infrastructure and systems to make the Polar LNG journeys safe and sound shortly. Beyond that, the Arctic sea corridors may alleviate the high LNG transit through the conventional routes and their chokepoints, but they are not a replacement for the conventional ones, not even with the most favorable conditions.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".