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Record W2972128163 · doi:10.1139/cjce-2019-0028

Improving engineering properties of mature fine tailings using <i>Tubifex</i>

2019· article· en· W2972128163 on OpenAlexaffvenue
Xiaojuan Yang, Miguel de Lucas Pardo, Maria Ibanez, Lijun Deng, Luca Sittoni, Ania C. Ulrich, Qun Chen

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTubifex tubifexTailingsTubifexDewateringGeotechnical engineeringEnvironmental scienceEcologyChemistryEnvironmental engineeringGeologyEnvironmental chemistryMaterials scienceBiologyMetallurgy

Abstract

fetched live from OpenAlex

The present study investigated the effects of Tubifex (Oligochaeta: Tubificidae) treatment on the dewatering process of mature fine tailings (MFT). Experiments testing the survival rate showed that Tubifex can survive at 20 °C and 4 °C. MFT with initial solids content (S c ) of 30% of total mass were treated in 11 settling columns by three Tubifex densities, 1400, 2000 and 4200 individuals·m −2 . Test results showed that the mean survival rate at 20 °C and 4 °C on the 28th day stayed around 85%. Tubifex enhanced MFT dewatering by providing compacted tailings with 11.6% and 66.7% higher S c and undrained shear strength compared with nontreated tailings. Tubifex accelerated pore water pressure dissipation. Tubifex did not affect the chemical composition of tailings except for a decrease in sulfate content. The S c of tailings treated by Tubifex increased by 67.4% within nine months, which was 129% greater than the S c increase of the nontreated tailings after 11 months.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.007
GPT teacher head0.148
Teacher spread0.141 · 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.

Study designSimulation or modeling
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

Citations3
Published2019
Admission routes2
Has abstractyes

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