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Record W4211108180 · doi:10.1139/cgj-2021-0209

Stabilization of muskeg soils using two additives: sand and urease active bioslurry

2022· article· en· W4211108180 on OpenAlexafffundvenue
Ahmed ElMouchi, Sumi Siddiqua, Emmanuel Salifu, Dharma Wijewickreme

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Applications in Construction Materials
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia, Okanagan Campus
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSoil waterVoid ratioCementation (geology)CompressibilityCalciteGeotechnical engineeringUreaseSoil scienceWater retentionEnvironmental scienceChemistryEnvironmental chemistryGeologyMineralogyMaterials scienceComposite materialCementThermodynamics

Abstract

fetched live from OpenAlex

Muskeg soils are considered problematic. They are distinguished by their high initial void ratio and water content. Therefore, they exhibit high compressibility and low shear strength when they are subjected to external loads. Microbially induced calcite precipitation (MICP) is a promising soil stabilization technique because it is considered environmentally friendly. In this study, the MICP technique using the urease active bioslurry approach was coupled with sand collected from a local source to stabilize muskeg soils. The effect of changing the sand percentage on the compressibility properties of muskeg soil was studied. The results showed that the addition of 10% sand and injection of two-pore volumes of cementation solutions significantly improved the compressibility properties such that the initial void ratio decreased by 70%.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

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)0.0120.000

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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 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

Citations7
Published2022
Admission routes3
Has abstractyes

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