Towards Establishing Targets for the Water Needs of Streams and Wetlands in Ontario, Canada
Bibliographic record
Abstract
Ontario has joined other jurisdictions around the world in assessing ecological flow assessment methodologies. The need to better manage water takings in the Province was the impetus for the work. It has been necessary to raise awareness of the need to move from consideration of single, minimum threshold flows to consideration of a flow regime that can maintain the ecological integrity of aquatic ecosystems. Pilot projects have been undertaken in several watersheds in southern Ontario to evaluate the applicability of various ecological flow assessment tools to assign instream flow requirements. Using a bottom up approach, a variety of methods are needed to identify the flow required to satisfy various ecological needs including those required to sustain communities of aquatic organisms; prevent disruption of geomorphic processes; achieve water quality objectives; and maintain connectivity. Historic flow, hydraulic and geomorphic methods were applied in the pilot studies. The Range of Variability Approach in combination with detailed hydrologic modeling was also applied to assess the acceptable departure from natural conditions within a top-down approach. Further work is required to evaluate the potential for various techniques to be transferred to areas of the Province with different climate, physiography, and development intensity. Regardless of the methods used to assign flow requirements, a framework is needed that allows for adaptive environmental management and refinement of techniques and targets as knowledge of ecosystem responses is gained.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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 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".