Effect of Mining on Fine Sediment Geochemistry in the Horsefly River Catchment, British Columbia, Canada: A Study on Black Creek Mine
Bibliographic record
Abstract
Canada has 7% of the world’s renewable freshwater and is also one of the top world producers of metals like uranium, gold and zinc. Consequently, it is not surprising that monitoring the environmental impacts of the country’s mining industry is in the interest of many. Mining exposes metals in sediments to weathering allowing the sediments to erode and redeposit elsewhere, most commonly in rivers, streams and lakes. As bed sediments from these surface waters retain, store or release heavy metals, those metals can be further transported, deposited and remobilised in either particulate or dissolved form. Previous studies have shown that most metals are in particulate form, specifically in the fine (<63 μm) sediment fraction.\nSediment geochemistry of gold mining was characterised and quantified to determine the spatial effects in the Horsefly catchment area of British Columbia, Canada, for the reason that the region has been extensively mined since the nineteenth century. Samples of channel bed sediments were collected from a creek near the abandoned Black Creek mine that drains into the Horsefly River. Sediment was also resuspended in the Horsefly River and collected with buckets and a continuous centrifuge. Both types of sediment were used to investigate spatial variability and trace any effects from the mine down along the creek and river. Heavy metal concentrations (arsenic, cadmium, copper, selenium and zinc) of the fine (<63 μm) sediments for each sample were quantified using aqua regia digestion and BCR’s (European Community Bureau of Reference) modified sequential ex- traction procedure and analysed by ICP-OES (inductively coupled plasma optical emission spectrometry). The percentage of organic matter and particle sizes were also determined. There were elevated levels of arsenic associated with the Black Creek mine in addition to local increases in arsenic concentrations along the Black Creek. Despite this, no recent mining effects were observed along the Horsefly River, which the Black Creek drains into, likely due to the mine’s inactive status and small size.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".