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Record W2332036250 · doi:10.1139/t2012-040

In situ measurements of cemented paste backfill at the Cayeli Mine

2012· article· en· W2332036250 on OpenAlexafffundvenue
B. D. Thompson, W.F. Bawden, Murray Grabinsky

Bibliographic record

VenueCanadian Geotechnical Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Toronto
FundersBarrick Gold Corporation
KeywordsGeotechnical engineeringPore water pressureHydrostatic equilibriumCementHydrostatic pressureMining engineeringShaft miningEngineeringGeologyForensic engineeringMaterials scienceComposite materialMechanics

Abstract

fetched live from OpenAlex

Cemented paste backfill (CPB) is accepted as the optimal backfilling material for many underground mines. However, the lack of in-stope backfill pressure data poses fundamental problems from both operational and research standpoints. In response to the requirement for in situ data, a comprehensive field instrumentation project has been conducted. Results are presented here for two stopes at the Cayeli Mine, where geotechnical instruments were installed at the barricades and throughout the stopes. Measurements from a large (slow rise rate) stope with high binder content CPB demonstrated a rapid departure from hydrostatic loading, resulting in relatively low barricade pressures. Conversely, data from a smaller (fast rise rate) stope with lower binder content CPB demonstrated that when cement hydration is retarded, high barricade pressures occur. These examples illustrate the relationship between CPB rise rate and the moderating effect of cement hydration on in situ pressures, which ultimately control barricade pressures. Once CPB gains shear strength, arching of pressures occurs. In situ pressures were reduced with proximity to stope walls and further, under stope access brows, demonstrating that barricade location influences barricade loads. The application of real-time pressure monitoring of pastefill barricades has been demonstrated as an important tool in optimizing operational backfilling efficiency.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.209
Teacher spread0.192 · 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 designObservational
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

Citations208
Published2012
Admission routes3
Has abstractyes

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Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207