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Record W2080578317 · doi:10.1080/17480930.2011.613567

Tracer tests to evaluate hydraulic residence time in limestone drains: Case study of the Lorraine site, Latulipe, Québec, Canada

2011· article· en· W2080578317 on OpenAlexaffabout
Abdelkabir Maqsoud, Bruno Bussière, Michel Aubertin, Benoît Plante, Johanne Cyr

Bibliographic record

VenueInternational Journal of Mining Reclamation and Environment · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsMinistry of Natural Resources and WildlifePolytechnique MontréalUniversité du Québec en Abitibi-TémiscamingueNatural Sciences and Engineering Research Council
Fundersnot available
KeywordsEffluentTRACERResidence time (fluid dynamics)Environmental scienceResidenceWater qualityDrainageHydrology (agriculture)Residence time distributionAcid mine drainageGeologyEnvironmental engineeringGeotechnical engineeringMineralogyMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Acid mine drainage (AMD) remains one of the major environmental problems for the mining industry. When AMD is produced on a mine site, passive treatment techniques such as limestone drains (LDs) can be used to improve water quality, particularly when the effluent is relatively small. In 1999, LDs were installed in combination with a cover with capillary barrier effects to rehabilitate the abandoned acid-generating Lorraine mine site in Quebéc, Canada. However, the quality of the water exiting the LD does not meet the local regulations (even if a significant improvement has been observed). To better understand the behaviour of the drains, the hydraulic residence time (HRT) was evaluated using various tracer tests. Tests’ results indicate that the HRT in the Lorraine LDs is close to the minimum value targeted at the design stage but is significantly different than those estimated from the geometrical characteristics and porosity of the drains and the water flow discharge.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.492
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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 teacher head, 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

Citations5
Published2011
Admission routes2
Has abstractyes

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