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Record W168168410

Effect of Mining on Fine Sediment Geochemistry in the Horsefly River Catchment, British Columbia, Canada: A Study on Black Creek Mine

2013· dissertation· en· W168168410 on OpenAlexaboutno aff
Deirdre E. Clark

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2013
Typedissertation
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentDrainage basinGeologyGeochemistryMining engineeringHydrology (agriculture)ArchaeologyGeographyGeomorphologyCartographyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.004
GPT teacher head0.180
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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