Systems Engineering Canada’s Oil Sands Resources and Its Future Impact on Global Oil Supply
Bibliographic record
Abstract
Approximately 2000 billion barrels of conventional oil may ultimately be extracted. We have soon consumed half of it. Global oil production may peak around 2010. It is claimed that non-conventional oil production, including Canadian oil sands production, may bridge the coming gap between the world’s oil demand and global oil supply. In 2003 the oil sands reserves were included in Canada’s estimated proven reserves, thus increasing from 5 to 180 billion barrels. The objective of this report is to investigate and analyse the production of heavy oil/bitumen from Canada’s oil sands deposits and its future impact on global oil supply. The report shows that the Canadian oil sands industry’s dependence on natural gas is unsustainable. Extensive use of bitumen for fuel and upgrading seems to be incompatible with Canada’s obligations under the Kyoto treaty. The Canadian oil sands industry should be viewed as two separate forms of oil production, in situ production (similar to conventional oil production) and mining. The long-term future of the Canadian oil sands industry is the in situ production,
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".