Geoelectrical Signatures of Acid-Generating Mine Waste Rock
Bibliographic record
Abstract
Acid mine drainage (AMD) contamination associated with waste rock piles (WRPs) at mining sites is a global concern, and understanding the generation and release of AMD from these piles is highly desirable. Traditional WRP monitoring techniques involve the installation of monitoring wells and periodic core sampling; however, these approaches are invasive, expensive and can only provide data with limited spatial and temporal resolution. An attractive alternative is non-invasive geophysical techniques that can provide non-invasive and continuous information on subsurface features and processes. This thesis aims to investigate the feasibility of the spectral induced polarization (SIP) method for monitoring changes in mine waste rock characteristics. Waste rock samples were obtained from three WRPs in the Sydney Coalfield in Nova Scotia, Canada. The properties of the waste rock were extensively characterized before kinetic column leaching and humidity cell experiments were performed on the samples with simultaneous tracking by SIP. Results show that the waste rock contained very low sulfide concentrations with SIP unable to capture distinct mineralogy changes during oxidation of the sulfides. However, SIP was extremely effective in monitoring the changes in the waste rock porewater characteristics associated with metal leaching and AMD flushing. Overall, this thesis improves our understanding of the capability of SIP to track changes in waste rock, while also introducing a robust approach for future experiments on waste rock and SIP.
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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".