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Record W2152683886 · doi:10.6310/jog.2009.4(3).5

RELIABILITY INDEX FOR SERVICEABILITY LIMIT STATE OF DRILLED SHAFTS UNDER UNDRAINED COMPRESSION

2009· article· en· W2152683886 on OpenAlexaboutno aff
Yu Wang

Bibliographic record

VenueRare & Special e-Zone (The Hong Kong University of Science and Technology) · 2009
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsServiceability (structure)Limit state designStructural engineeringEngineeringGeotechnical engineeringReliability (semiconductor)

Abstract

fetched live from OpenAlex

In recent years, reliability-based design (RBD) has gradually gained popularity in geotechnical engineering. Several RBD codes have been developed and implemented around the world that calibrate ultimate limit state (ULS) designs for a target ULS reliability index (βuls). However, the serviceability limit state (SLS) design still is considered using conventional deterministic approaches with an unknown SLS reliability index (βsls). This paper makes use of a relationship between βsls and βuls to infer the βsls of drilled shafts under undrained compression from the βuls that is specified already in the design codes. The values of βsls are estimated for drilled shafts designed in accordance with three different design methods (i.e., semi-empirical analysis using in situ and laboratory test data, analysis using static loading test results, and analysis using dynamic monitoring results) of the National Building Code of Canada (NBCC). The results indicate that, for the undrained compression capacity of drilled shafts designed in accordance with the NBCC, the designs automatically fulfill the corresponding SLS design requirements.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.004
GPT teacher head0.180
Teacher spread0.176 · 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 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

Citations2
Published2009
Admission routes1
Has abstractyes

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Same venueRare & Special e-Zone (The Hong Kong University of Science and Technology)Same topicGeotechnical Engineering and Underground StructuresFrench-language works237,207