Reservoirs\nof Selenium in Coal Waste Rock: Elk Valley,\nBritish Columbia, Canada
Bibliographic record
Abstract
Selenium (Se) reservoirs in coal\nwaste rock from the Elk Valley,\nsoutheastern British Columbia, the location of Canada’s major\nsteelmaking coal mines, were characterized and quantified by analyzing\nsamples collected from the parent rock, freshly blasted waste rock\n(less than 10 days old), and aged waste rock (deposited between 1982\nand 2012). Se is present throughout the waste rock dumps at a mean\ndigestible (Se<sub>D</sub>) concentration of 3.12 mg/kg. Microprobe\nanalyses show that Se is associated with the primary minerals sphalerite,\npyrite, barite, and chalcopyrite and secondary Fe oxyhydroxides. Selenium\nK-edge X-ray absorption near-edge spectroscopy analyses indicate that,\non average, 21% of Se is present as selenide (Se<sup>2–</sup>) in pyrite and sphalerite, 19% of Se is present as selenite (Se<sup>4+</sup>) in barite, 21% of Se is present as exchangeable Fe oxyhydroxide\nand clay-adsorbed Se<sup>4+</sup>, and 39% of Se is present as organoselenium\nassociated with coaly matter. The dominant source minerals for aqueous-phase\nSe are pyrite and sphalerite. Secondary Fe oxyhydroxide sequesters,\non average, 37% of Se released by pyrite oxidation. Measured long-term\nSe fluxes from a rock drain at the base of a waste dump suggest that\nat least 20% of Se<sup>2–</sup>-bearing sulfides were oxidized\nand released from that dump over the past 30 year period; however,\nthe Se mass lost was not evident in Se<sub>D</sub> analyses.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.085 | 0.001 |
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; both teacher heads agree on what is shown here.
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".