Water, Water Everywhere, But Just How Much is Clean?: Examining Water Quality Restoration Efforts Under the United States Clean Water Act and the United States-Canada Great Lakes Water Quality Agreement
Bibliographic record
Abstract
If asked to describe what an endangered species is, the average American could likely give a rough definition. Perhaps the World Wildlife Federation and its iconic panda logo comes to mind, or perhaps a favorite endangered species studied in elementary school. But what about an 'endangered' river or lake? A definition or an example of an at-risk water body may be more difficult for the average American to describe. While not 'endangered' under the same definition as an endangered species, water bodies across the North American continent have been designated as 'impaired' or an 'Area of Concern' under United States and Canadian legislation. Regulation of water is of the utmost importance due to the great demands on this resource. A classic example of the importance of water comes from its role in living things. Water comprises up to 60% of the human body, and some organisms derive up to 90% of their body weight from water. Water bodies are an important resource for human survival because they provide drinking water and support species that humans consume, including aquatic species, land animals, and crops. Water is also crucial to support economic activity, as it is a vital component of industry, energy, agriculture, and transportation. The water used in each of these important functions must meet certain quality standards in order to adequately and safely support human survival.
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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 | 0.006 | 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".