The use of hay and sawdust to promote the removal of selenium and nitrate in coal mine drainage: A saturated up flow column experiment
Bibliographic record
Abstract
A saturated up-flow column experiment was conducted to compare the ability of locally-available organic amendments (hay and sawdust) to foster reducing conditions and attenuate permit-exceeding concentrations of sulfate, nitrate, and selenium in effluent from a British Columbia coal mine. Mine effluent was continuously passed through columns containing one or both amendments mixed with mine-sourced rock, and indicators of organic decomposition and redox conditions were quantified in influent and effluents. Over the 180-day trial, effluent from hay-amended columns exhibited the highest removal of target parameters (up to 99.9%, 98.6%, and 77.5% removal of nitrate, selenium, and sulfate, respectively), although performance decreased over time, suggesting possible long-term performance concerns. In contrast, sawdust-amended columns fostered only partial denitrification and no sulfate removal, which could be linked to the more recalcitrant nature of the organic matrix. Effluents from all columns amended with organics would require further treatment before discharge to a receiving environment.
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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) | 0.001 | 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".