Microbiological and geochemical characterization of As-bearing tailings and underlying sediments
Bibliographic record
Abstract
Over the past 100 years, extensive oxidation of As-bearing sulfide-rich tailings from the abandoned Long Lake Gold Mine (Canada) has resulted in the formation of acid mine drainage (pH 2.0–3.9) containing high concentrations of dissolved As (∼400 mg L−1), SO42-, Fe and other metals. Dissolved As is predominantly present as As(III), with increased As(V) near the tailings surface. Pore-gas O2 is depleted to < 1 vol% in the upper 30–80 cm of the tailings profile. The primary sulfides, pyrite and arsenopyrite, are highly oxidized in the upper portions of the tailings. Elevated proportions of sulfide-oxidizing prokaryotes are present in this zone (mean 32.3% of total reads). The tailings are underlain by sediments rich in organic C. Enrichment in δ34S-SO4 in pore-water samples in the organic C-rich zone is consistent with dissimilatory sulfate reduction. Synchrotron-based spectroscopy indicates an abundance of ferric arsenate phases near the impoundment surface and the presence of secondary arsenic sulfides in the organic-C beneath the tailings. The persistence of elevated As concentrations beneath the tailings indicates precipitation of secondary As sulfides is not sufficient to completely remove dissolved As. The oxidation of sulfides and release of As is expected to continue for decades. The findings will inform future remediation efforts and provide a foundation for the long-term monitoring of the effectiveness of the remediation program.
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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".