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Record W2055629462 · doi:10.1139/t06-112

Dewatering of mine tailings using electrokinetic geosynthetics

2007· article· en· W2055629462 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Geotechnical Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsTailingsDewateringConsolidation (business)Geotechnical engineeringEnvironmental scienceElectrokinetic phenomenaWaste managementEngineeringMining engineeringMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Many mining operations produce tailings that dewater very slowly under self-weight consolidation. One way of reducing the water content of such tailings is by electroosmotic dewatering. Although the technique has been used with some success in civil engineering applications, it is still largely seen as a solution of last resort. This is probably due to the high energy costs reported in the literature, as well as problems of very rapid corrosion of metal electrodes. This paper describes a study using newly developed electrokinetic geosynthetics (EKGs) as electrodes for the in situ dewatering of mine tailings. Laboratory tests were undertaken on mineral sands tailings in both a purpose-built testing cell and a laboratory testing tank using EKGs, followed by an outdoor experiment in a tank containing approximately 9 m 3 of the tailings. This test was run for over 2 months. Energy consumption in the outdoor test was less than 1 kWh per dry tonne of material dewatered and there was no sign of electrode deterioration even after 2 months of usage. The results point to a potentially powerful technique for reducing the water content of tailings ponds in situ, thus increasing storage space, improving stability, and facilitating closure of these facilities.Key words: tailings, dewatering, electroosmosis, electrokinetic geotextiles, consolidation.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.218
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