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Record W2330231147 · doi:10.1061/9780784412787.098

A Benchmark Slope For System Reliability Analysis

2013· article· en· W2330231147 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

VenueGeo-Congress 2013 · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsDalhousie University
FundersAustralian Research Council
KeywordsProbabilistic logicReliability (semiconductor)Slope stabilityReliability engineeringBenchmark (surveying)Computer scienceSlip (aerodynamics)Random variableMathematicsStatisticsGeotechnical engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

In a probabilistic slope stability analysis, the failure probability associated with the most critical slip surface (the one with the minimum reliability index) is known to be smaller than that obtained for the system as a whole where all potential slip surfaces are considered. System slope reliability has been studied in recent years by several probabilistic methods, including the Random Finite Element Method (RFEM), Limit Equilibrium Methods (LEM) combined with First Order Reliability Methods (FORM), and Response Surface Methods (RSM). The only one of these methods that can properly account for spatial variability however is the RFEM. In this paper, we set up a benchmark slope for system reliability analysis and compare the probability of failure obtained both with and without inclusion of spatial variability. The paper will give recommendations for the types of slope reliability problems that benefit from proper consideration of spatial variability.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.180
Teacher spread0.177 · 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