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Record W7161776231 · doi:10.82308/53835

Determination des parametres mecaniques des remblais miniers faits de residus cimentes

2001· dissertation· fr· W7161776231 on OpenAlexaboutno aff
Stéphane. Servant

Bibliographic record

Venuenot available
Typedissertation
Languagefr
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsCoringSampling (signal processing)Work (physics)Sample (material)Characterization (materials science)Instrumentation (computer programming)

Abstract

fetched live from OpenAlex

A field trial was conducted to demonstrate the applicability of a self-boring pressuremeter probe for in situ testing of cemented paste backfill. This technology proved to be efficient in evaluating behaviour of in situ conditions of mine backfill underground. Effectively, laboratory experience shows that it is not possible to insure that all physical and mechanical conditions prevailing underground are respected when samples are prepared and tested in the lab. Moreover, sampling by coring backfill underground proved to be sometimes not very efficient and the question of sample disturbance is a major concern. This thesis aims at presenting the considerations leading to the probe selection and the technical aspects related to conducting pressuremeter tests in an underground mine. A preliminary analysis of the experimental pressuremeter curves is presented with the derived in situ properties obtained from a paste backfill in a Canadian mine. It is shown that the selected instrument fulfilled the main objective of the project, which was the in situ characterization of a paste backfill. Recommendations are given for future applications of this testing technique for mine backfill and improve the efficiency of the work underground. Also, recommendations are given to improve test analysis and consequently the quality of the results obtained with the self-boring pressuremeter technique.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.251
Teacher spread0.231 · 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 designOther design
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

Citations0
Published2001
Admission routes1
Has abstractyes

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