Characterization and metal availability of copper, lead, antimony and zinc contamination at four Canadian small arms firing ranges
Bibliographic record
Abstract
Backstop soils of four small-arms firing ranges (SAFRs) of the Canadian Force Bases (CFBs) were characterized in terms of their total soil Cu, Pb, Sb and Zn concentrations, grain size distribution, mineralogy, chemical properties, vertical in-depth contamination distribution (for one CFB), and scanning electron microscope (SEM-EDS) characterization. Metal availability from the soils was evaluated with three leaching tests: the toxicity characteristics leaching procedure (TCLP), representing a landfill leachate; the synthetic precipitation leaching procedure (SPLP), representing field conditions; and the gastric juice simulation test (GJST), representing the leachate of the human stomach during the digestive process and, therefore, the potential metal transfer to humans in the case of soil ingestion. Metal analyses of soils and leaching test extracts were conducted with an Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES) instrument. Total soil results showed maximal concentrations of 27,100 mg/kg for Pb, 7720 mg/kg for Cu, 1080 mg/kg for Zn, and 570 mg/kg for Sb. The SEM-EDS analysis showed significant amounts of lead carbonates, which resulted from the alteration of the initial metallic Pb particles. Metal availability evaluation with the leaching tests showed that TCLP Pb and Sb thresholds were exceeded. For the SPLP and the GJST, the drinking water thresholds of the Ministère du Développement Durable, de l'Environnement et des Pares (MDDEP) of Quebec were exceeded by Pb and Sb. The metal availability assessment showed that SAFR backstop soils may pose a potential risk to the environment, groundwater and humans, and affect the management of such soils in order to minimize potential metal dispersion in the environment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".