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Acid rock drainage source control opportunities at the Red Dog Zinc and Lead Mine, USA

2011· article· en· W2287310478 on OpenAlexaff
J. Caleb Clark, David R. Christensen, Boris Lum

Bibliographic record

VenueMine closure · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsTeck (Canada)
Fundersnot available
KeywordsZincLead (geology)DrainageAcid mine drainageMining engineeringEnvironmental scienceZinc compoundsGeologyMetallurgyMaterials scienceEcologyBiologyGeomorphology

Abstract

fetched live from OpenAlex

Located in the Western Brooks Range of Alaska, the Red Dog Mine is one of the most northerly active, zinc-lead open pit mines. Mining of high grade zinc and lead sulphide ores results in the production of waste rock that is mostly acid generating. Control and treatment of acid rock drainage (ARD) from waste rock and pit walls is one of the most critical environmental activities at the mine site. The treatment of ARD water from the main waste rock stockpile, containing total dissolved solids (TDS) values as high as 90,000 mg/L, is expensive today and it will be a major component of post-closure costs in the future. In order to reduce the amount of water to be treated in the near and longer term, Red Dog has initiated programs to minimise the production of ARD at the source, through construction of engineered cover systems on waste rock stockpiles and will make improvements in the collection and treatment of the ARD waters from the stockpiles, to allow for more efficient removal of TDS from the impacted waters.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.026
GPT teacher head0.221
Teacher spread0.195 · 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 designNot applicable
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

Citations2
Published2011
Admission routes1
Has abstractyes

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