Water Quality Effects from an Aquaculture Operation in a Meromictic Iron Pit Lake in Northwestern Ontario, Canada
Bibliographic record
Abstract
Abstract In 1989, aquaculture for the production of rainbow trout (Oncorhynchus mykiss) was started in the upper depths of the 180-m deep Caland pit lake formed after the flooding of the former Steeprock Iron Mine. After ten years of operation, water quality was shown to be affected by the fish farm as well as proximal waste and the surficial geology of the area. Meromictic conditions occurred in the pit lake with a dichotomy in water quality versus depth. A cluster of parameters (ammonia, total phosphorus, total Kjeldahl nitrogen, dissolved organic carbon, B, pH, dissolved oxygen) were either in higher concentrations in the mixolimnion or varied little throughout the entire water column, and a second cluster of parameters had higher levels below the chemocline (conductivity, alkalinity, dissolved inorganic carbon, total dissolved solids, nitrate, sulfate, Ca, Mg, hardness, Na, Cl, K, Fe, Mn, Sr, and silicon dioxide). Statistically significant variations in concentrations among many of these chemical parameters were observed between the two years of study, among depths, and among seasons. Nutrient loading from excess fish food and waste increased phosphorus and ammonia levels. The expansion of the fish farm also reduced the levels of dissolved oxygen in the lower depths of the pit lake, thus reducing the volume of usable water for aquaculture purposes. In the early 2000s the fish farm decreased production and those closed in 2006. Later data showed that nitrate and potassium had corresponding decreases in both the monimolimnion and the mixolimnion. Sulfate levels remained elevated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".