11. Exploring Various Factors and Sources in Relation to Environmental Contaminants in the Rideau Canal System
Bibliographic record
Abstract
The Rideau Canal has served several purposes since its establishment in 1832. Acting as a channel connecting Ottawa and Kingston, it was often used for the transport of commercial goods and lumber. Over time, its uses expanded to include recreational purposes such as: sport fishing, boating, cottaging, and tourism. This increased development and use has caused the Rideau Canal and its watersheds to become vulnerable to metal contamination. Studies within Dr. Linda Campbell’s Lab at Queen’s University have shown that cadmium (Cd), lead (Pb), chromium (Cr), zinc (Zn), mercury (Hg), arsenic (As), and copper (Cu), are in concentrations that have reached or exceeded the level of potential concern for both aquatic and human health. This study explores the potential sources as well as both natural and human factors which could be related to the influx in metal contaminants within the system. A literature review of both historical and recent documents was completed and supplemented with personal interviews with professionals and community members. Based on these investigations, the primary sources being reviewed are: atmospheric deposition, natural geological processes, and anthropogenic factors relating to residential development. While research is still ongoing preliminary analysis suggests that these are the primary sources of contamination within the area.
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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 | 0.006 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".