Mackenzie Delta LNG Transport and Ice Management Study
Bibliographic record
Abstract
Abstract This paper will study the LNG Transport opportunities from the Canadian Arctic to the Asian markets. Mackenzie Delta LNG (MDLNG) project is in the Canada's Northwest Territories (NWT) which contains publicly owned conventional natural gas reserves which could be developed for export that would provide immediate economic benefit to the Inuvialuit Settlement Region, NWT and Canada. This paper presents the results of a feasibility study undertaken to evaluate the shipping routes and ice conditions along the route from the Arctic to the Asian LNG markets. Arctic LNG carriers have been in use in the Russian Arctic for years already and we have been deeply involved in the design, development, and testing of those current LNG carriers. Russian rules are somewhat different and thus the operations would commence in Canada and US waters that would give some opportunities in the LNG Carrier design as well. In this paper we will go through the general differences in the LNG carriers design for MDLNG. Currently the plan is to build gravity-based structure (GBS) to the offshore MacKenzie Delta. The GBS would need additional ice management support and vessels. In this paper we would talk about ice management vessels needed to support the operations for loading the LNG carriers as well as talk about the recommended ice management operations. With modern technology, good design and planning, it can be shown that the LNG transportation by ships is a feasible solution compared to building pipelines across the Arctic.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".