Arsenic fate in the historic Cobalt Mining Camp, Ontario: Geochemical, mineralogical, and vegetation-related controls on metal(loid) mobility
Bibliographic record
Abstract
This study investigates the controls on metal(loid) mobility from mine tailings and pond sediments near Cobalt, Ontario with a focus on arsenic (As), which is present at high concentrations throughout this former mining district. Mineralogical and geochemical analyses were performed on tailings from four abandoned mill sites and nearby pond sediments. The mass of readily soluble metal(loid)s in the tailings and sediments was evaluated using shake flask experiments. Horsetails ( Equisetum spp.) growing on these tailings were collected for chemical characterization, backscattered electron imaging, and synchrotron-based chemical analysis. Results indicate that mineralogical hosts of As vary between depositional environments. Authigenic, oxidized phases (e.g., erythrite and an iron- and calcium-bearing arsenate) sequester As in near-surface environments. Ore minerals (e.g., cobaltite and safflorite) and authigenic reduced phases (e.g., realgar) host As in submerged tailings and anoxic pond sediments. Short-term exposure of tailings and sediments to oxidized, ultrapure water releases As from the ore minerals and reduced phases (1.31–325 mg L −1 As; median = 19.1 mg L −1 As). Horsetails growing on these tailings sequester As via formation of an oxidized iron-bearing plaque on the outside of the plant roots and shoots. This study demonstrates that As mobility in mine-impacted environments is controlled by geochemical reactions, mineral dissolution and precipitation, and vegetation growth. These processes must be considered when developing long-term management decisions for legacy mine sites.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".