Stormwater: Monitoring and Adaptive Management in the Metro Vancouver Region
Bibliographic record
Abstract
The Metro Vancouver region’s Integrated Liquid Waste and Resource Management Plan includes a regulatory requirement that links community planning to watershed health. The Province requires municipalities to develop Integrated Stormwater Management Plans for watersheds within their boundaries by 2014. In 2012, an intergovernmental and multi-disciplinary working group was tasked with developing a consistent program to monitor hydrological, biological and chemical indicators of watershed health. The program would be used by municipalities of different sizes, drainage patterns and budgets. The working group members are drawn from representatives of Metro Vancouver and its Environmental Monitoring Committee (EMC), Stormwater Interagency Liaison Group (SILG), and British Columbia Ministry of Environment. The Metro Vancouver region’s weight of evidence Adaptive Management Framework was developed to provide guidance for Metro Vancouver municipalities for development of watershed monitoring programs to enable reporting out to the Ministry of Environment on a biennial basis regarding the effectiveness of watershed-based planning initiatives and the health of their watersheds. If the Ministry of Environment is satisfied that the monitoring approach proposed by the Adaptive Management Framework could result in improvement of Integrated Stormwater Management Plans and protect stream health, the deadline for municipal completion of these plans may be extended from 2014 to 2016.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".