Impact of Variability in Precipitation Patterns on the Geochemistry of Pyritic Uranium Tailings Rehabilitated with Saturated Cover Technology
Why this work is in the frame
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Bibliographic record
Abstract
Increasing variability in precipitation patterns is expected to result from climate change in Canada. This effect has the potential to affect the performances of saturated covers in inhibiting acid rock drainage (ARD) and metal leaching (ML) processes. Because ARD and ML may cause the release of deleterious chemical species into the environment, such climate-change-driven impact was investigated using trickle leach columns. The physical, chemical, and mineralogical characteristics of the tailings as well as chemical composition of the leachate were measured before and after the column study. Results from the experiment showed that higher variability in precipitation regimes could enhance leaching of uranium. Leaching ranged from 67.1 to 90.1% of the total amount of U, with greater values associated with higher variability in precipitation patterns. Lower water levels and prolonged drought periods led to higher oxygen fluxes to the U tailings and dissolution of carbonate-bearing minerals. The release of carbonates could have enhanced uranium leaching through the formation of stable uranium-carbonate complexes in solution. Overall, this study shows that water level variation caused by varying precipitation patterns can significantly affect the drainage chemistry of saturated cover systems for which the level fluctuates freely near the tailings–cover interface.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it