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Record W3168334557 · doi:10.1080/19236026.2021.1919010

Cover systems and landforms for rehabilitation of mine waste storage facilities: Practical insights

2021· article· en· W3168334557 on OpenAlexaffabout
Bryan Ayres

Bibliographic record

VenueCIM Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsLandformCover (algebra)RehabilitationWaste managementEnvironmental scienceEnvironmental planningMining engineeringConstruction engineeringBusinessEngineeringGeologyMedicineMechanical engineeringGeomorphology

Abstract

fetched live from OpenAlex

Modern management of mine waste storage facilities (MWSFs) often requires that they be decommissioned with a cover system. In addition to creating a self-sustaining landscape that supports the end land use, cover systems are intended to reduce long-term risks to human and ecological receptors from the underlying waste to acceptable levels. The performance and longevity of a cover system will be strongly influenced by the features and geometric configuration of the MWSF final landform. Cover systems and landforms must therefore be thought of as an integrated design. The elements of greatest importance in the design process for long-term sustainability of MWSF final landforms/cover systems based on the author’s experience are noted in this article. Several key items that must be considered and addressed during the planning phase of constructing a MWSF final landform are also described. Key aspects associated with rehabilitating a tailings impoundment and waste rock pile at the former Cluff Lake uranium mine in Saskatchewan are included to illustrate many of the practical insights detailed in this article.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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
Published2021
Admission routes2
Has abstractyes

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Same venueCIM JournalSame topicTailings Management and PropertiesFrench-language works237,207