The Canadian Oil Sands Industry Under Carbon Constraints
Bibliographic record
Abstract
We investigate the impact of climate policies on Canada’s oil sands industry, the largest of its kind in the world. Deriving petroleum products such as gasoline and diesel from oils sands involves significant amounts of energy, and that contributes to a high level of CO2 emissions. We apply the MIT Emissions Prediction and Policy Analysis (EPPA) model, a computable general equilibrium model of the world economy, augmented to include detail on the oil sands production processes, including the possibility of carbon capture and storage (CCS). We find: (1) without climate policy, annual Canadian bitumen production increases almost 4-fold from 2010 to 2050; (2) with climate policies implemented in developed countries, Canadian bitumen production drops by 32% to 68% from the reference 4-fold increase, depending on the viability of large-scale CCS implementation, and bitumen upgrading capacity moves to the developing countries; (3) with climate policies implemented worldwide, the Canadian bitumen production is significantly reduced even with CCS technology, which lowers CO2 emissions at an added cost. This is mainly because upgrading bitumen abroad is no longer economic with the global climate policies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".