Bibliographic record
Abstract
The Point Sources project of the Geological Survey of Canada's Metals in the Environment Initiative (1997 - 2002) examined the distribution of metals in various environmental sampling media around three Canadian metal smelters at Rouyn-Noranda (Quebec), Belledune (New Brunswick), and Trail (British Columbia). This bulletin contains eleven papers on the studies made at Rouyn-Noranda and one paper on work at the Belledune smelter. Regional surveys of snow, soil, lake sediment, peat, and vegetation were used to characterize and understand metal dispersal around the Horne smelter at Rouyn-Noranda. Metals emitted by the Horne smelter are transported by the atmosphere and radially dispersed around this point source. The resulting smelter footprint, i.e. where metal concentrations are significantly higher than ambient background levels, shows exponentially decreasing values with increasing distance from the source in various environmental media (snow, soil, peat, lake sediment, trees). Snow data provide information about metal loading (deposition rates) in winter conditions. The most recent growth of peat hummocks provides independent estimates of metal loading over one year. Loading data (modelled as a function of distance from the smelter) provide estimates of the total tonnage of metal deposited within (and close to) the footprint for comparison with emission data. The distribution of metals in marine sediments near the Brunswick lead smelter is controlled by both atmospheric and oceanographic processes. The influence of the emissions on metal levels in coastal sediments near Belledune extends at least 20 km from the smelter.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.149 | 0.094 |
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".