Reservoirs of Selenium in Coal Waste Rock: Elk Valley, British Columbia, Canada
Bibliographic record
Abstract
Selenium (Se) reservoirs in coal waste rock from the Elk Valley, southeastern British Columbia, the location of Canada's major steelmaking coal mines, were characterized and quantified by analyzing samples collected from the parent rock, freshly blasted waste rock (less than 10 days old), and aged waste rock (deposited between 1982 and 2012). Se is present throughout the waste rock dumps at a mean digestible (SeD) concentration of 3.12 mg/kg. Microprobe analyses show that Se is associated with the primary minerals sphalerite, pyrite, barite, and chalcopyrite and secondary Fe oxyhydroxides. Selenium K-edge X-ray absorption near-edge spectroscopy analyses indicate that, on average, 21% of Se is present as selenide (Se(2-)) in pyrite and sphalerite, 19% of Se is present as selenite (Se(4+)) in barite, 21% of Se is present as exchangeable Fe oxyhydroxide and clay-adsorbed Se(4+), and 39% of Se is present as organoselenium associated with coaly matter. The dominant source minerals for aqueous-phase Se are pyrite and sphalerite. Secondary Fe oxyhydroxide sequesters, on average, 37% of Se released by pyrite oxidation. Measured long-term Se fluxes from a rock drain at the base of a waste dump suggest that at least 20% of Se(2-)-bearing sulfides were oxidized and released from that dump over the past 30 year period; however, the Se mass lost was not evident in SeD analyses.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".