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Record W2321888244 · doi:10.14288/1.0042683

Regulatory considerations for historic mine remediation in BC : Atlin Ruffner Mill and Tailings case study

2014· article· en· W2321888244 on OpenAlexaff
Joanna Runnells, Gregg G. Stewart

Bibliographic record

VenuecIRcle (University of British Columbia) · 2014
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTailingsMillEnvironmental remediationMining engineeringCopper mineEnvironmental scienceWaste managementEngineeringMetallurgyContamination

Abstract

fetched live from OpenAlex

A large number of historic mine sites across British Columbia are no longer operating and no responsible person exists or can be found. The clean-up of historic mine sites is undertaken as per provisions within the Environmental Management Act (EMA), and particularly the Contaminated Sites Regulation (CSR) and the Hazardous Waste Regulation (HWR). The Crown Contaminated Sites Program (CCSP) of the BC Ministry of Forests, Lands and Natural Resource Operations leads the management of contaminated provincial lands where the province has accepted responsibility. The CCSP identifies and prioritizes sites using a science-based and risk assessment approach to reduce risks to human health and the environment. Using the Atlin Ruffner Mill and Tailings Site as a case study, the application of the CSR and the HWR to the remediation of a historic mill and tailings will be discussed. The site is approximately 20 km from Atlin, BC and produced silver, lead, and zinc as well as gold, copper, cadmium, molybdenum, and tin. Prior to remediation, the mill and tailings site included a mill building with machinery and ore storage bins, two leveled areas (upper and lower mill pads), two trailers, a shack, an explosives shed, a tailings pond, two settling ponds, and an adit with flowing drainage. Prior to remediation, the site was classified as High Risk under the CSR and metals in soils and mine wastes were classified as leachable hazardous waste under the HWR, requiring special permitting to be managed on site. The paper will focus on the application of the CSR and HWR to the mine site.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.001
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.163
Teacher spread0.154 · 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 designQualitative
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
Published2014
Admission routes1
Has abstractyes

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