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Record W1998133801 · doi:10.1002/nag.222

Probabilistic analysis of underground pillar stability

2002· article· en· W1998133801 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2002
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsDalhousie University
FundersNational Science Foundation
KeywordsPillarStability (learning theory)Probabilistic logicGeotechnical engineeringSafety factorMonte Carlo methodReliability (semiconductor)Context (archaeology)Finite element methodCompressive strengthRandom fieldFactor of safetyStructural engineeringEngineeringSlope stabilityMathematicsComputer scienceGeologyStatisticsMaterials science

Abstract

fetched live from OpenAlex

Abstract The majority of geotechnical analyses are deterministic, in that the inherent variability of the materials is not modelled directly, rather some ‘factor of safety’ is applied to results computed using ‘average’ properties. In the present study, the influence of spatially varying strength is assessed via numerical experiments involving the compressive strength and stability of pillars typically used in underground construction and mining operations. The model combines random field theory with an elasto‐plastic finite element algorithm in a Monte‐Carlo framework. It is found that the average strength of the rock is not a good indicator of the overall strength of the pillar. The results of this study enable traditional approaches involving factors of safety to be re‐interpreted as a ‘probability of failure’ in the context of reliability based design. Copyright © 2002 John Wiley & Sons, Ltd.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

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

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 head0.046
GPT teacher head0.340
Teacher spread0.295 · 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