Wetland ecohydrology monitoring at TRCA: insights and lessons learned
Bibliographic record
Abstract
The Wetland Water Balance project seeks to develop tools, knowledge, and guidelines to support TRCA's (Toronto and Region Conservation Authority's) stormwater management criteria for water balance analyses where these are required for the protection of wetlands. This includes tools to better characterize the pre-development hydrology of a wetland and the components of the water balance that may contribute to maintenance of important ecological functions. As part of this project, a number of wetlands across TRCA and Credit Valley Conservation jurisdictions have been instrumented to learn how to: a) efficiently characterize baseline conditions, and; b) over the longer-term, develop a better understanding of wetland hydrological functions in the landscape and how these may relate to ecological functions. This presentation will focus on the preliminary results from the regional monitoring study, as well as physical monitoring techniques for characterizing shallow groundwater dynamics in wetlands. This research will help TRCA achieve its objectives of maintaining and enhancing the existing natural heritage system in the watersheds of greater Toronto by informing stormwater management system design and future water resource management decisions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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 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".