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Record W4380682850 · doi:10.3390/min13060806

Optimization of Soil-Sludge Mixtures by Compaction for Potential Use in Mine Site Reclamation

2023· article· en· W4380682850 on OpenAlexafffund
Mamert Mbonimpa, Élysée Tshibangu Ngabu, Tikou Belem, Ousseynou Kanteye, Abdelkabir Maqsoud

Bibliographic record

VenueMinerals · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
FundersFonds de recherche du Québec – Nature et technologiesIAMGOLD
KeywordsHydraulic conductivitySoil waterLand reclamationCompactionWater contentWater retention curveEnvironmental scienceDrainageSettlingSoil scienceEnvironmental engineeringGeotechnical engineeringGeologyEcology

Abstract

fetched live from OpenAlex

Studies have indicated the potential of mixtures of silty soil and sludge produced by active treatment of acid mine drainage for use in covers with capillary barrier effects for mine site reclamation. Very high water contents of sludge in the settling pond could negatively affect the required hydrogeotechnical properties of soil sludge mixtures with high sludge contents. The challenge is then to determine the optimum wet sludge content of soil-sludge mixtures with air entry values (AEV) and/or saturated hydraulic conductivity (ksat) required for use in mine site reclamation covers. This paper presents a method to determine the optimum wet sludge content βopt for obtaining the maximum dry density of compacted soil-sludge mixtures. Two types of soil (S1 and S2) and two types of sludge (A and W) were tested. It was observed that βopt can be determined when the initial water content of the soil used in the mixture is lower than the optimum water content determined from the Proctor curve of the soil alone (10 wt% and 6 wt% for soils S1 and S2, respectively) and that βopt does not change with increasing initial soil water content. Optimum wet sludge contents found were low (≈15 wt% and ≈7 wt% for mixtures containing soils S1 and S2, respectively) for the test conditions, indicting a limited quantity of reusable sludge in the mixtures. For all mixtures, the water content corresponding to βopt was close to the optimum water content of the soil alone. Results of soil water retention and saturated hydraulic conductivity (ksat) tests conducted on selected optimized mixtures indicated that the mixtures based on soils S1 and S2 have air entry values higher than 20 kPa and would be suitable for use in the moisture retention layer of covers with capillary barrier effects, while soil S2 and the derived mixtures exhibited ksat < 10−7 cm/s and would be potential materials for the low permeability layer in low saturated hydraulic conductivity covers.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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 designBench or experimental
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

Citations4
Published2023
Admission routes2
Has abstractyes

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