Diavik Waste Rock Project: Evolution of Mineral Weathering, Element Release, and Acid Generation and Neutralization during a Five-Year Humidity Cell Experiment
Bibliographic record
Abstract
A five-year, humidity-cell experiment was used to study the weathering evolution of a low-sulfide, granitic waste rock at 5 and 22 °C. Only the rock with the highest sulfide content (0.16 wt %) released sufficient acid to overcome a limited carbonate acid-neutralization capacity and produce a substantial decline in pH. Leached SO4 and Ca quickly increased then decreased during the first two years of weathering. Sulfide oxidation continued to release acid and SO4 after carbonate depletion, resulting in an increase in acid-soluble elements, including Cu and Zn. With the dissolution of Al-bearing minerals, the pH stabilized above 4, and sulfide oxidation continued to decline until the end of the experiment. The variation in activation energy of sulfide oxidation correlates with changes in sulfide availability, where the lowest activation energies occurred during the largest releases of SO4. A decrease in sulfide availability was attributed to consumption of sulfide and weathered rims on sulfide grains that reduced the oxidation rate. Varying element release rates due to changing carbonate and sulfide availability provide identifiable geochemical conditions that can be viewed as neutralization sequences and may be extrapolated to the field site for examining the evolution of mineral weathering of the waste rock.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".