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In situ monitoring for ground truthing paste backfill designs

2010· article· en· W2885663559 on OpenAlexafffund
Murray Grabinsky

Bibliographic record

VenuePaste/˜Pœaste · 2010
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooUniversity of TorontoBarrick Gold Corporation
KeywordsGeotechnical engineeringLiquefactionMining engineeringRock blastingGeologyRock mass classificationCuring (chemistry)Pore water pressureMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Optimised geomechanical design of cemented paste backfill systems requires feedback on the actual field performance of paste fills and their barricades during filling, subsequent curing, and exposure to ongoing mining activities. A comprehensive monitoring strategy is described and its application is demonstrated for five stopes at three different mining operations. Important information is revealed about several poorly understood phenomena including stress arching within the fill mass, barricade pressure reduction with increasing setback from the stope, temperature induced stresses, and liquefaction potential of paste fill due to production blasting and rockbursts. Consideration is given to optimised monitoring procedures that other engineers could use to investigate similar phenomena at their mines.

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)
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 score0.421
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 communication0.0000.001
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 head0.030
GPT teacher head0.234
Teacher spread0.204 · 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 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

Citations31
Published2010
Admission routes2
Has abstractyes

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