A geoscientific perspective on airborne smelter emissions of metals in the environment: an overview
Bibliographic record
Abstract
Historically, smelters have been a major source of metals and SO 2 released to the environment in Canada. The study of emissions in the environment around smelters is therefore a priority in evaluating policies in relation to sustainable development. This Special Issue is devoted to papers on various projects supported under three Canadian programmes on metals in the environment. Scientific questions addressed by these programmes include understanding how emitted metals impact the surface environment in different settings, estimating the smelter outputs of metals, distinguishing smelter-derived releases from geogenic contributions, and understanding the fate of current emissions of metals and metalloids and their accumulation during the twentieth century. The approach of the scientific team involved characterizing the spatio-temporal distribution of smelter-emitted metals in the plume and in various surficial media around selected Canadian smelters. This overview paper summarizes some of the findings discussed in the Special Issue, specifically that: (1) smelter-emitted metal-bearing solids have characteristics that allow their quantification and permit the evaluation of their contribution to the metal load of natural media; (2) delineation of smelter ‘footprints’ can be approached by mathematical estimation or by measurement of multi-element or isotope ratios; and (3) investigation of archival geological systems provides time series that reflect the point-source inputs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".