Integrated Analyses of Canada's Water Resources: A System Dynamics Approach
Bibliographic record
Abstract
An integrated water resources management model for Canada, CanadaWater, has been developed using the system dynamics simulation approach. The CanadaWater model takes into consideration dynamic interactions between quantitative characteristics of the available water resources and water use that are determined by the socio-economic development level, population and physiographic features of Canadas territory. It is a unique tool that integrates the water quantity and quality sectors with seven sectors that drive economic development: population; agricultural development; food production; capital investment; energy generation; use of non-renewable resources; and persistent pollution. The CanadaWater model is a system dynamics simulation model that provides for investigation of different scenarios. Model simulations are performed for 12 scenarios designed to investigate policy options in the area of fresh water availability, wastewater treatment, economic growth, population growth, energy generation and food production. The conclusions point to a very strong dependence of Canadas future development and well being on maintaining acceptable quality of the water resources and controlling the level of water use in different sectors.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".