Bibliographic record
Abstract
Use of Liquified Natural Gas (LNG) has been growing rapidly in the Asia-Pacific region, mainly as an energy source for electric generation but also for distribution to residential, commercial, and industrial consumers. Growth in LNG use has been strongest in Japan, Korea, and Taiwan, which together accounted for 86% of Asia-Pacific LNG trade in 2009. China and India, which are also becoming important LNG markets, represented 13% of LNG trade in the region in 2009 but are expected to account for an even greater share in coming years.LNG prices in the Asia Pacific region are generally indexed to the Japan Customs Cleared price for crude oil imports, which closely follows the price of Brent (North Sea) crude oil. Because LNG prices there are approximately 90% of the oil price on an equivalent-heating-value basis, they are considerably higher than North American gas prices. LNG exports to Asia would allow Canadian gas producers to benefit from this price differential.Until now, Canadian gas producers have only exported gas via pipeline to markets in the United States. However, it is becoming difficult to maintain (let alone grow) export volumes to the United States because US gas production has increased remarkably as the result of technologies that have made development of tight gas and shale gas resources commercially viable. Moreover, this increase in the United States’ domestic supply of gas has reduced gas prices and, similarly, netbacks to producers exporting gas to the United States.Fortunately, Canadian gas producers have an opportunity to develop markets in Asia where buyers are seeking stable, long-term LNG purchase agreements with reliable gas producers in politically stable countries such as Canada.However, a variety of policies stand to impede development of the infrastructure that will be required to export liquefied natural gas (LNG) to markets in the Asia-Pacific region via British Columbian ports. Most of the natural gas supplies are expected to come from northeast British Columbia, which has an immense amount of tight and shale gas resources. However, some of the gas could eventually also be brought from northwest Alberta, the southeast corner of Yukon, and other regions.To assess the economic impacts from exporting LNG to markets in the Asia-Pacific region, we developed a development scenario compatible with the National Energy Board’s most recent long-term forecast of BC natural gas production.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.051 | 0.012 |
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".