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Record W3173816976 · doi:10.1139/cgj-2020-0657

Evaluation of flow liquefaction and liquefied strength using the cone penetration test: an update

2021· article· en· W3173816976 on OpenAlexvenueno aff
P.K. Robertson

Bibliographic record

VenueCanadian Geotechnical Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringLiquefactionCone penetration testPenetration testSoil waterGeologyDrainageSoil liquefactionClay soilPenetration (warfare)Shear strength (soil)EngineeringSoil scienceSubgrade

Abstract

fetched live from OpenAlex

A method to evaluate the susceptibility of soils to undrained strength loss that could result in flow liquefaction as well as a method to estimate the resulting liquefied undrained shear strength of predominately sand-like soils using the cone penetration test (CPT) were outlined by Robertson in 2010. Based on published data and recent case histories, this technical note describes a recommended update to these methods to estimate the large-strain liquefied or remolded undrained shear strength for both sand-like and clay-like soils as well as soils that transition from sand-like to clay-like. The proposed update acknowledges that soil behavior can vary from sand-like to clay-like and that CPT interpretation to estimate large-strain undrained shear strength changes due to the changing drainage conditions during the CPT. The updated method builds upon previously published data combined with recent experience and case histories.

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)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0140.006
Science and technology studies0.0010.003
Scholarly communication0.0040.004
Open science0.0050.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.005

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 head0.023
GPT teacher head0.240
Teacher spread0.217 · 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 designObservational
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

Citations38
Published2021
Admission routes1
Has abstractyes

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