Developing an Integrated Water Management Tool for Winnipeg River’s Hydropower System
Bibliographic record
Abstract
Hydropower is a renewable, economic, and low-emission source of energy and has the flexibility to accommodate different electricity demands. The Province of Manitoba’s current electricity supply is about 97% generated by hydropower, making it potentially vulnerable to climate change. The increase in the annual mean temperature in the Canadian Prairies is twice the rise in the global mean temperature, influencing precipitation patterns which ultimately highlights the importance of understanding the impacts of climate change in Manitoba. A MODSIM-DSS model has been developed for the operation of water control structures and hydropower facilities along the Winnipeg River, including the Rainy and English Rivers, which contains 11% of the hydropower capacity in Manitoba. This simulation model is equipped with parametric rule curves representing the operation of control points in the system. These rule curves are calibrated and evaluated against historically measured and observed data. To better understand potential adaptation responses, the simulation model will be used to project the response of this hydropower system to future climate conditions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".