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Record W3201558639 · doi:10.36487/acg_repo/2115_34

Paste backfill thermal contraction: Red Lake operations case study

2021· article· en· W3201558639 on OpenAlexaff
Jeffrey Oke, Katie Hawley, Tikou Belem, Ali Saadatmand Hashemi

Bibliographic record

VenuePaste/˜Pœaste · 2021
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsContraction (grammar)ThermalMaterials scienceGeotechnical engineeringEnvironmental scienceGeologyMeteorologyPhysics

Abstract

fetched live from OpenAlex

One of the earliest attempts at field measurement within hydraulically placed cemented backfill occurred over 20 years ago. Recently, Thompson et al. (2014a) published their findings on capturing thermal expansion within cemented paste backfill (CPB) and cemented hydraulic backfill (CHB). They discovered that the total earth pressure within the CPB following placement is likely to increase at a rate of 30 kPa/°C (i.e. for an 11°C temperature increase). However, Thompson and his co-authors' research did not elaborate on the subsequent effects of thermal dissipation (or thermal contraction) in backfill. A comprehensive literature study concluded with no clear evidence of thermal dissipation phenomenon and its effects in backfill. It is hypothesised by the authors that if thermal expansion can occur, then thermal dissipation or contraction is also likely to occur. Red Lake operation (RLO) of Evolution Mining conducted a field program to capture the characteristics of the CPB during a transition from a plug–cure–main pour strategy to a more aggressive pour strategy (i.e. continuous pour operation). During this investigation, strong evidence of thermal contraction was observed in three of the four instrumented stopes. This paper presents detailed findings of two of the instrumented stopes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score1.000

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)0.0010.000

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 head0.019
GPT teacher head0.221
Teacher spread0.201 · 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 designSimulation or modeling
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

Citations3
Published2021
Admission routes1
Has abstractyes

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