Petitcodiac Watershed Water Quality Monitoring
Bibliographic record
Abstract
Since 1999, the Petitcodiac Watershed Alliance (PWA) has been sampling water to monitor various water quality parameters throughout the Petitcodiac Watershed to gauge the health of our local ecosystem. The objective of our long-term water quality monitoring remains to identify sources of water pollution to help us and our stakeholders improve water quality within the Petitcodiac and Memramcook River watersheds. To fulfill this objective, we collect annual data at 20 long-term monitoring sites once a month from May to October on the following parameters: dissolved oxygen, pH, specific conductivity, total dissolved solids, salinity, water temperature, turbidity, total coliforms, Escherichia coli (E.coli), nitrates and phosphates. Results are compared to relevant water quality guidelines and past data to infer trends in water quality measurements, which allows us to speculate on the potential causes for each parameter’s fluctuations and relationships, and prepare remedial plans when necessary. The PWA engages with community members to improve riparian buffer zones in urban and rural areas and promote best management practices related to watershed management. This program would not be possible without our key funder, the New Brunswick Environmental Trust Fund, and other important funders such as the Government of Canada and RBC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".