Insulation covers with capillary barrier effects to control sulfide oxidation in the Arctic
Bibliographic record
Abstract
Insulation covers can be used for the reclamation of tailings storage facilities located in the Arctic. However, this approach can be vulnerable to changes in climatic conditions as its long-term performance is based strictly on controlling the temperature of tailings. A more robust alternative could be the use of insulation covers with capillary barrier effects because they control both the tailings temperature and oxygen flux. This study assesses the potential for an insulation cover with capillary barrier effects using laboratory tests and a field experimental cell. Material characterization indicated that the fine-grained compacted waste rock is a suitable material for constructing a moisture-retaining layer. A 2 m thick field experimental cell was constructed in which temperatures and unfrozen volumetric water contents were monitored for 3.5 years. Results showed thaw depths periodically reaching the reactive tailings and temperatures at the tailings–cover interface greater than 0 °C for 39–57 days each year. The degree of saturation in the moisture-retaining layer was almost always greater than 80%–85% when temperatures at the tailings–cover interface exceeded 0 °C. Yearly oxygen fluxes passing through the moisture-retaining layer were calculated to be less than 2 mol/m2/year, thus confirming the effectiveness of the cover as an oxygen barrier.
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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 | 0.000 |
| 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) | 0.000 | 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".