Occurrence and mobility of thiolated arsenic in legacy mine tailings
Bibliographic record
Abstract
We studied the occurrence of dissolved thiolated Arsenic (As) in legacy tailings systems in Ontario and Nova Scotia, Canada, and used aqueous and mineralogical speciation analyses to assess its governing geochemical controls. Surface-accessible and inundated tailings in Cobalt, Ontario, contained ∼1 wt-% As mainly hosted in secondary arsenate minerals (erythrite, yukonite, and others) and traces of primary sulfide minerals (cobaltite, gersdorffite and others). Significant fractions of thiolated As (up to 5.9 % of total dissolved As) were detected in aqueous porewater and surface water samples from these sites, comprising mostly monothioarsenate, and smaller amounts of di- and tri-thioarsenates as well as methylated thioarsenates. Tailings at the Goldenville and Montague sites in Nova Scotia contained less (<0.5 wt-%) As, hosted mostly in arsenopyrite and As-bearing pyrite, than the Cobalt sites, but exhibited higher proportions of dissolved thiolated As (up to 17.3 % of total dissolved As, mostly mono- and di-thioarsenate and traces of tri-thioarsenate). Dissolved thiolated As was most abundant in sub-oxic porewaters and inundated tailings samples across the studied sites, and its concentrations were strongly related to the prevailing redox conditions and porewater hydrochemistry, and to a lesser extent, the As-bearing mineralogy. Our novel results demonstrate that thiolated As species play an important role in the cycling of As in mine waste systems and surrounding environments, and should be considered in mine waste management strategies for high-As 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".