Bibliographic record
Abstract
The objective of the Clean Water Act (CWA) is to maintain and restore the chemical, physical and biological integrity (ecological integrity) of the Nation's waters. However, in populated urban watersheds with large amounts of imperviousness, loss of riparian cover, extensive habitat modifications, altered hydrology and numerous pollutant and runoff sources, achieving the highest level of ecological integrity may no longer be feasible — attempting to do so may set unrealistic goals and be economically unachievable. Under the CWA and federal regulations, States, territories and Tribal Nations have the capability to set realistic goals for managing urban water bodies. These goals are the State and Tribal water quality standards and should be the primary yardstick by which water quality management, including storm water management is measured. Through the public water quality standards-setting process, States, territories and Tribes can make improvements in managing aquatic life by adopting more appropriate aquatic life uses for urban water bodies and setting different levels of criteria for protecting each use. Key tools in this effort are biological assessments and criteria. This paper discusses the statutory background and essential elements of water quality standards and how biological assessments and criteria can be used to define appropriate aquatic life goals for urban water bodies and better focus scarce resources on restoration efforts that are attainable.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.043 | 0.009 |
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; both teacher heads agree on what is shown here.
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".