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Record W2603732384 · doi:10.1061/9780784480489.014

A Framework for Evaluating the Effects of Drained Cyclic Preshearing on the Liquefaction Resistance of Ottawa Sand

2017· article· en· W2603732384 on OpenAlexaboutno aff
Erin L. D. Sibley, Scott M. Olson, Carmine P. Polito

Bibliographic record

VenueGeotechnical Frontiers 2017 · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsLiquefactionGeotechnical engineeringShear (geology)AmplitudeVolume (thermodynamics)Constant (computer programming)GeologyRelative densityMaterials scienceEnvironmental scienceComposite materialPhysicsMicrostructureComputer scienceOptics

Abstract

fetched live from OpenAlex

A series of cyclic simple shear tests were conducted on reconstituted specimens of clean, fine-grained Ottawa C109 sand at three relative densities. Small-amplitude drained cyclic preshearing strains of 0.02-0.3% were applied to the specimens for 30-1000 cycles. After drained cyclic preshearing, the specimens were subjected to higher amplitude cyclic shear strains under constant-volume conditions until liquefaction occurred. The test results are compared with constant-volume cyclic shear tests without preshearing to evaluate the influence that strain amplitude and the number of cycles of drained cyclic preshearing have on the liquefaction resistance of Ottawa C109 sand. Based on this comparison, a framework for understanding drained preshearing is proposed.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.279
Teacher spread0.259 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations4
Published2017
Admission routes1
Has abstractyes

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