Effect of local sources on metal concentrations in littoral sediments and aquatic macroinvertebrates of the St. Lawrence River, near Cornwall, Ontario
Bibliographic record
Abstract
Concentrations of Cd, Cr, Cu, Fe, Hg, Ni, Pb, and Zn were measured in surface sediments and in five aquatic macroinvertebrate taxa to assess metal contamination in ecologically important but understudied shallow littoral areas of the St. Lawrence River, near Cornwall, Ontario, and to test for the effect of local point sources. Metal concentrations in littoral sediments were generally below the lowest effect level of the Ontario provincial sediment quality guidelines and were positively related to the proportion of fine particles and of organic matter in sediments. Analyses of the spatial distribution of metal concentrations in sediments and macroinvertebrates showed that local sources of Hg and Zn had contributed to the contamination of littoral sediments and macroinvertebrates. Concentrations of Cr, Fe, Ni, and Zn in chironomids and oligochaetes were similar or higher than levels reported for deeper sites in the Cornwall area, despite the much lower concentrations in littoral sediments, suggesting a higher bioavailability of metals in littoral than in deeper sediments. Although the effect of local point sources of metals was still detectable in 1994, the comparison with Ontario sediment quality guidelines and with other sites in the Great Lakes - St. Lawrence ecosystem suggests that metal contamination of littoral sediments and invertebrates was relatively low.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".