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Record W1509533093

Effect of Electric Field Intensity On Electro-cementation of Caissons In Calcareous Sand

2006· article· en· W1509533093 on OpenAlex
Amnart Rittirong, Julie Q. Shang, Mostafa A. Ismail, Mark Randolph

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUWA Profiles and Research Repository (UWA) · 2006
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsCementation (geology)CalcareousElectric fieldGeotechnical engineeringIntensity (physics)CaissonGeologyMaterials scienceComposite materialCementOpticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Effects of the electric field intensity on electro-cementation of offshore calcareous sand are studied via large-scale model tests and electric field analyses. In the experiments, the model caissons were embedded in noncemented calcareous sand recovered from the Western Australia coast, and a DC intermittent electric field was applied via a central electrode placed inside the caisson. The development of cementation in soil during electrokinetic treatment was monitored through soil shear wave measurements. After 7 days of electrokinetic treatment, the pullout resistances of the caisson model embedded in calcareous sand increased up to 105%. Significant soil cementation was observed in the vicinity of soil-caisson interfaces, which was confirmed by electro-microscopic images. The results of the performed electric field analyses show that the formation of cementing constituents in soil is directly related to the intensity of the applied electric field.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.004
Threshold uncertainty score0.405

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)0.0000.000

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 head0.290
Teacher spread0.282 · 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