Abstract: Geochemical trends in a river receiving treated mine water, Bathurst, New Brunswick
Bibliographic record
Abstract
Effluent from the tailings ponds at the Brunswick No. 12 mine has been discharged into Little River since 1964. Jn 1993, a water treatment plant began operation, resulting in decreased metal concentrations and increased pH in the effluent released to Little River. Following implementation of the water treatment process, water sampling along the river indicated a decrease in pH downstream. This research examines the trend in pH and other geochemical parameters observed along the river. The mine is situated at the headwaters of the south branch of Little River. The discharge in the south branch is dominated by effluent from the water treatment plant. The length of the river from the mine to its discharge point in the Bathurst Basin is approximately 22 km. Aqueous geochemical and stream-sediment sampling were completed from June to August, 1998. Results of this sampling reveal a correlation between suspended and dissolved metal concentrations {Pb, Zn, S) in the upper reaches of the south branch of Little River, and elevated metal concentrations (Pb, Zn) in the river sediments (45J 25μm fraction) . Decreases in alkalinity, dissolved oxygen and pH were observed in the first 1-2 km downstream of the water treatment plant. Alkalinity and dissolved oxygen rise to background values within 2 km of their respective minimum, whereas the pH recovered to an average value of 6.3. This pattern is consistent with the release of low concentrations of acidity {Fe or intermediate sulfur oxidation species) from the water treatment plant. In association with these trends in pH, metals transported in the stream are transforred between the aqueous phase and adsorption sites on suspended sediment particles.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".