Comparison of metal distributions in snow, peat, lakes and humus around a Cu smelter in western Quebec, Canada
Bibliographic record
Abstract
Concentrations of metals around the Cu smelter at Rouyn-Noranda, Québec, in snow, peat, the humus horizon of soil, lake water and sediments, show generally similar spatial distribution patterns. The contours of smelter-related metal concentrations in all these media are approximately circular in shape, centred on the smelter, and elongated somewhat towards the east due to the prevailing wind direction. Close to the smelter, the concentrations are up to 1000 times greater than regional background levels. The distances at which concentrations of smelter-related metals decrease to background levels is in the range 65 ± 5 km. The ratio of (Cu+As)/(Al+Fe) is a useful indicator of source apportionment for comparing the results between sampling media because it is independent of measurement units and maximizes the contrast between smelter and non-smelter materials. The value of the ratio, which changes as a function of distance from the smelter, reflects the mixing and dilution of emissions with non-smelter dust and aerosols. Deposition rates of metal calculated for snow and peat integrated over the area of the smelter-centred anomaly allow estimates to be made of the amounts of metal deposited from the smelter, after correcting for deposition of background metal. The proportions of reported metal emissions accounted for by deposition within 150 km of the smelter are: Cu, 25–50%; Pb, 10–20%; Zn, 25%; As, 5%; and Cd 20–25%. Metals in excess of these proportions are probably transported outside the immediate smelter footprint, but deposition of smelter-emitted metals becomes so small at these distances, and so mixed with airborne metals from other sources, that it is difficult to discriminate between smelter and non-smelter sources in samples taken on the ground.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".