ENERGY FOR YUKON: THE NATURAL GAS OPTION Executive Summary Background
Bibliographic record
Abstract
Yukon has one of the highest economic growth rates in Canada driven in large part by investment in the mining sector. Sustaining this growth requires a reliable and competitive price source of energy. Yukon has abundant natural gas resources. This initiative, Energy for Yukon (E4Y): The Natural Gas Option, examines the feasibility of developing Yukon’s significant natural gas resources to meet Yukon’s current and future energy demands and examines what is required to develop these valuable resources. As stated in the Energy Strategy for Yukon: “The government’s strategy for oil and gas is focused on how to best develop Yukon’s resources and also meet Yukon’s energy needs.”1 Unless new sources of renewable energy are developed, the current alternative is diesel generation which is costly and contrary to Yukon’s Climate Change Action Plan. Reliance on diesel to meet future demand may stall proposed mining projects (due to cost) and likely increase the cost of energy for residential and commercial customers. It would also significantly increase Yukon’s greenhouse gas (GHG) emissions. This paper summarizes the findings of this initiative and suggests next steps. In doing so it presents Yukon’s requirements for energy and the available energy options to enable continued
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".