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Record W2107551908 · doi:10.6310/jog.2009.4(3).3

Calibration of Information-Sensitive Partial Factors for Assessing Earth Slopes

2009· article· en· W2107551908 on OpenAlexaff
Gwang-Ha Roh, Han Hong

Bibliographic record

VenueJournal of geoengineering · 2009
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsSlope stabilityReliability (semiconductor)Probabilistic logicCohesion (chemistry)Reliability engineeringCalibrationConsistency (knowledge bases)Factor of safetyLimit state designMathematicsComputer scienceStatisticsGeotechnical engineeringStructural engineeringEngineeringGeometry

Abstract

fetched live from OpenAlex

Use of the limit state design with the calibrated load and resistance factors (or partial factors of safety) has a long tradition, especially for structural design codes. The load and resistance factors are calibrated using statistics, reliability, probabilistic analyses and selected target safety levels. To take advantage of the reliability-based design approach, to achieve a greater consistency in the safety level for designed or assessed earth slopes, and to cope with the degree of uncertainty in soil properties, in this study, calibration of the information-sensitive partial factors is carried out. The calibration is based on the first-order reliability method, and considers that the critical slip surface for a given set of soil properties and geometric variables of slope can be estimated based on the generalized method of slices. The calibrated factors depend on the degree of uncertainty in the soil properties (i.e., coefficients of variation of cohesion and friction angle), and on the selected target reliability levels. Results of calibration are used to develop empirical equations for estimating the partial factors that are to be used for slope stability analysis and to assess the adequacy of slope for a selected target safety level. It is hoped that the developed relations could be used to aid the development of reliability-consistent design and checking of earth slopes, and to promote the practical application of the limit state design in geotechnical engineering.

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 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: none
Teacher disagreement score0.770
Threshold uncertainty score0.457

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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2009
Admission routes1
Has abstractyes

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