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Record W2947912494

An investigation into the time dependent deformation behaviour of open pit slopes at Gibraltar Mine, BC, Canada

2018· dissertation· en· W2947912494 on OpenAlexaboutno aff
John Danielson

Bibliographic record

VenueSummit (Simon Fraser University) · 2018
Typedissertation
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsMining engineeringOpen-pit miningGeologyGeographyArchaeologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Open pit slope instabilities experience a sequence of decelerating deformation events following changes in stress state due to blasts or mining. These deformation events are poorly understood. This thesis uses large databases of specific energy and slope radar monitoring data to characterise five slope instabilities. Eight different rheological and empirical curve-fitting models are applied to 24 deformation events to identify which model best approximates observed deformation. The best-performing model, the Fractional Maxwell model, is then applied to nearly 200 deformation events identified from the five slope instabilities. The resulting model parameters α, fractional viscosity, and A, magnitude of the response, are tracked and compared with deformation history, instability size and geometry, and blast size and location. Slope instabilities exhibit increasingly viscous behaviour with deformation as damage accumulates within the rock mass. The magnitude and likelihood of deformation events correlate with the proximity of the stress change to critical geological 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.126

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 science0.0000.000
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 head0.008
GPT teacher head0.197
Teacher spread0.188 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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