Cost-benefit analysis of Kitimat Liquified Natural Gas project of British Columbia
Bibliographic record
Abstract
The Kitimat Liquid Natural Gas project (KMLNG) represents a substantial opportunity for several major players in the BC Natural gas sector and many are excited at the possibilities of the proposed KMLNG and possible economic activity to follow. Recently the companies Apache, EnCana, and EOG resources cleared final government environmental approval to move to the final stage of application to make the KMLNG a reality. The KMLNG will include the construction of a 463 km pipeline project between Summit Lake BC and Kitimat as well involved the construction of the LNG plant itself. The natural gas resource that these companies are extracting comes with many consequences both positive and of management concern for the province. Considerations regarding green-house gas emissions, ecological impacts, water consumption from hydraulic fracturing, and long-term site degradation are all considerations that are not accounted for in financial calculations for the KMLNG. This project will examine the Net Present Value of KMLNG from the social perspective for British Columbia and compare this to the value expected for the companies Apache, EnCana and EOG resources on a go forward basis. This project will examine both the financial aspects of KMLNG for industry and contrast this with the value of KMLNG from the social perspective. This project will contrast the positive economic benefits with the cost of the ongoing gas industry developments in British Columbia. The problem with the current economic condition is that the price of natural gas is low due to excess supply in North America. With Canada's first LNG export project completed, access to energy-hungry Asian markets could change the economic equation dramatically. --P. ii.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".