Bibliographic record
Abstract
Energy security and greenhouse gas reduction are thought to be two of the most urgent priorities for sustaining and improving the human condition in the near future. Few places pit the two goals so directly in opposition to one another as the Alberta oil sands. Here, Canadian natural gas is burned in massive quantities to extract oil from one of North America’s largest native sources of carbon-intensive heavy oil. However, this conflict need not continue. Nonemitting nuclear energy can replace natural gas as a fuel source in an economical and more environmentally sound way. This would allow for the continued extraction of transportation fuels without greenhouse gas emissions, while freeing up the natural gas supply for hydrogen feedstock and other valuable applications. Bitumen production in Alberta expanded dramatically in the past 5 years as the price of oil rose to record levels. This paper explores the feasibility and economics of using nuclear energy to power future oil sands production and upgrading activities, and puts forth several nuclear energy application scenarios for providing steam and electricity to in situ and surface mining operations. This review includes the Enhanced CANDU 6, the Advanced CANDU Reactor, and the pebble bed modular reactor. Based on reasonable projections of available cost information, steam produced using nuclear energy is expected to be less expensive than steam produced by natural gas at current natural gas prices and at prices above $6.50/MMBtu (CAD). For electricity production, nuclear energy becomes competitive with natural gas plants at gas prices of $10–13/MMBtu (CAD). Costs of constructing nuclear plants in Alberta are affected by higher local labor costs, which this paper took into account in making these estimates. Although a more definitive analysis of construction costs and project economics will be required to confirm these findings, there appears to be sufficient merit in the potential economics to support further study.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".