Recovery of Acid and Metal Damaged Lakes near Sudbury, Ontario: Trends and Status. Cooperative Freshwater Ecology Unit Report
Bibliographic record
Abstract
deposition of pollutants from over a century of operations at the Sudbury area metal smelters. The lakes closest to the smelters, which historically received very high deposition of both acid and metal particulates, were the most severely affected. Smelter emissions were greatly reduced in the 1970's, lake water quality began to improve, and some recovery of biological communities was observed. Further reductions in smelter emissions during the 1990's have been accompanied by continuing improvements in aquatic habitat quality, but the evaluation of lake responses to emission controls is complicated by the interaction of lake acidity and metal concentrations with other factors. Weatherrelated variations in storage and release of sulphur from lake catchments appear to greatly influence patterns of chemical recovery. Despite the dramatic water quality improvements observed to date, some lakes are still acidic and elevated levels of copper, nickel, and other metals persist in the water and sediments of many lakes. Very positive evidence of biological recovery is emerging for many groups of aquatic biota including zooplankton, phytoplankton, benthic invertebrates and fish. However, severely damaged biological communities have often been slow to recover, in part reflecting continuing habitat quality limitations. Future recovery of lakes close to Sudbury from the effects of acidification and metal contamination will also be influenced by the effects of other local
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".