Analysis of the cost effectiveness of alternative policies and technologies to manage water extractions by the oil sands sector along the lower Athabasca River
Bibliographic record
Abstract
The Lower Athabasca Water Management Framework limits water extractions by the oil sands industry near Fort McMurray, Alberta. To increase water-use efficiency and minimise the cost of water restrictions, several policy and technology options were developed and assessed using quantitative and qualitative methods. Selected options were the policies of water trade and pricing with refund, and the technologies of storage, and consolidated tailings and increased recycling. Options were designed based on year 2020 demand and assessed relative to prior allocation. Using linear programming and static optimisation, it is shown that an off-stream storage sized to avoid water restrictions, in combination with efficient water allocation (e.g. water trade), is most cost-effective, although provides no ongoing incentive to increase water-use efficiency. Only the policy options provide equal incentives across firms to increase efficiency. To achieve both objectives of increased water-use efficiency and minimised costs, a combined policy and technology approach is recommended.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".