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Record W2983603719 · doi:10.1680/jgere.19.00029

Characterisation of fibre-reinforced backfill/rock interface through direct shear tests

2019· article· en· W2983603719 on OpenAlexafffund
Xiangqian Xu, Mamadou Fall, Imad Alainachi, Kun Fang

Bibliographic record

VenueGeotechnical Research · 2019
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsMaterials scienceDirect shear testComposite materialShear (geology)Cementation (geology)MicrostructureCuring (chemistry)Shear stressGeotechnical engineeringCementGeology

Abstract

fetched live from OpenAlex

This paper reports on the results of a laboratory investigation on the shear behaviour of the interface between granite rock and cemented paste backfill (CPB) reinforced with different amounts of fibre (F-CPB) and cured at room temperature for different lengths of time by performing direct shear tests. Moreover, various microstructural analysis techniques are also used to characterise the degree of cementation of the cemented matrix, as well as the microstructure of the interface. The results indicate that the shear properties and behaviour of the F-CPB/rock interface are a function of the fibre content (optimal fibre content) and reduce the contraction at the interface. It is also found that the optimal fibre content is a function of the curing time and applied normal stress. The shear strength envelopes indicate that the friction angle at the interface is larger in the sample that contains fibres, whereas fibre reinforcement reduces the interface adhesion. The results of this research will contribute to improvements in the design and stability assessments of fibre-reinforced cemented-backfill structures.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.318
Teacher spread0.269 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

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