Bright spots among lakes in the Rideau Valley Watershed, Ontario
Bibliographic record
Abstract
Water quality, of critical importance to the ecological and social health of lake ecosystems, is maintained through complex interactions within lakes as well as between lakes and their watersheds. Often, water quality is managed by working toward improved water clarity, however, our ability to predict water clarity, and to manage lakes for it, is not always as successful as desired. Regional strategies for water clarity improvement often overlook the role of local environmental stewardship actions performed by lake associations on individual lakes across a region. Lake associations can act through directly altering biophysical drivers of clarity or the way that residents act within the system, demonstrating great potential to be incorporated into successful lake scale water quality management plans. We used a "bright spots" lens, in which we focus on those lakes whose water quality is higher than expected, to investigate the relationship between lake associations and water quality on 39 lakes in the Rideau Valley Lake Region (Ontario, Canada). We found that lake associations that are linked to "bright spot" lakes operate in a distinctly different way than other groups in the region, focusing on networking and advocacy activities instead of on ecological management. This points to the importance of working toward networking and advocacy goals as a future for lake stewardship groups in the Rideau Valley and other stewardship groups adapting this approach to their own social-ecological contexts.
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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) | 0.002 | 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 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".