Cumulative Impacts/Risk Assessment of Water Removal or Loss from the Great Lakes-St. Lawrence River System
Bibliographic record
Abstract
Abstract The Great Lakes and St. Lawrence River are a source of water for many communities and industries around their shores. A portion of this water removed from the lakes is consumed and not returned. There is a strong potential that consumption of water will increase in the future. In addition, there is concern that water could be removed from the Great Lakes for export to other countries. Any removal of water from the Great Lakes that is not returned will lower water levels in the lakes and St. Lawrence River. It is anticipated that warmer conditions may result from anthropogenic climate change, which could cause a further lowering of Great Lakes-St. Lawrence water levels. A qualitative evaluation was undertaken of the potential impacts of decreased water levels and of the risks posed by these impacts. Les Grands Lacs et le fleuve St-Laurent alimentent en eau de nombreuses agglomérations et industries situées sur leurs rives. Une partie de l’eau provenant des Grands Lacs n’y retourne pas. La consommation d’eau risque fort d’augmenter dans l’avenir et on appréhende que de l’eau puisée dans les Grands Lacs soit exportée. Le niveau d’eau dans les Grands Lacs et du St-Laurent s’abaissera si l’on n’y retourne pas l’eau utilisée. Le réchauffement climatique causé par les activités humaines pourrait abaisser davantage le niveau d’eau des Grands Lacs et du St-Laurent. C’est pourquoi on a entrepris une évaluation qualitative des répercussions possibles d’une diminution des niveaux d’eau et des dangers qui peuvent en découler.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".