MétaCan
Menu
Back to cohort
Record W2508010100 · doi:10.1139/cgj-2016-0265

Effect of embedment on consolidated undrained capacity of skirted circular foundations in soft clay under planar loading

2016· article· en· W2508010100 on OpenAlexvenueno aff
Cristina Vulpe, Susan Gourvenec, Alexander F. Cornelius

Bibliographic record

VenueCanadian Geotechnical Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
FundersLloyd's Register
KeywordsEmbedmentGeotechnical engineeringConsolidation (business)Bearing capacityPlanarFinite element methodOffshore geotechnical engineeringGeologySurface finishEngineeringStructural engineeringMaterials scienceComposite materialComputer science

Abstract

fetched live from OpenAlex

The effect of foundation embedment ratio and soil–skirt interface roughness on the consolidated undrained capacity of skirted circular foundations under planar loading in normally consolidated clay has been investigated through coupled three-dimensional finite element analyses. Results are presented as failure envelopes, and changes in shape and size of the normalized vertical–horizontal–moment (VHM) failure envelopes are described as a function of relative magnitude and duration of applied preload. Results show that embedment ratio and interface roughness affect the load distribution within the soil mass, but that consolidated undrained capacity under planar loading scales proportionately with the (unconsolidated) undrained capacity of the foundation. This latter feature enables the results to be neatly synthesized into a relatively straightforward method for use in engineering practice for prediction of gain in undrained VHM capacity due to preload and consolidation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.009
GPT teacher head0.216
Teacher spread0.206 · 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

Citations32
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and AnalysisFrench-language works237,207