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Record W2089851069 · doi:10.1680/envgeo.14.00023

Improving control of contamination from waste rock piles

2014· article· en· W2089851069 on OpenAlexaff
Stefan Broda, Michel Aubertin, Daniela Blessent, Eugenia M. Hirthe, Thomas Graf

Bibliographic record

VenueEnvironmental Geotechnics · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsHydrogeologyGeotechnical engineeringDrainageGeologyInfiltration (HVAC)PileEnvironmental scienceMaterials science

Abstract

fetched live from OpenAlex

Waste rock piles are made of heterogeneous, coarse-grained rock extracted from mines to reach the ore. The internal structure of a pile has a major impact on water and oxygen movement and hence the production of acid mine drainage or contaminated neutral drainage. This paper illustrates potential avenues to minimise the infiltration of precipitation into the core zone of rock piles by applying a compacted layer on top of each bench, made of finer-grained non-reactive waste rock. Several configurations and characteristics (without and with cover, inclined and horizontal covers, varying hydrogeological properties of the cover material) are evaluated using the numerical three-dimensional fully integrated variably saturated flow model HydroGeoSphere. In these simulations of a single bench, the compacted layer is represented as being homogeneous and isotropic while the loose core waste rock zone is represented using two approaches: (i) the classic equivalent porous media approach and (ii) a medium with randomly generated fractures to represent the effect of macropores on water flow. Short (10 d) and longer-term (1 a) simulations have been conducted with recharge events based on historic observations. The results provide guidelines for the design of efficient compacted layers leading to an improved environmental response of waste rock piles.

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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.003

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.167
Teacher spread0.163 · 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
GenreMethods

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

Citations18
Published2014
Admission routes1
Has abstractyes

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