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Record W2320694291 · doi:10.1520/gtj104317

Effect of Sample-Preparation Method on Critical-State Behavior of Sands

2012· article· en· W2320694291 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeotechnical Testing Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern University
Fundersnot available
KeywordsShearing (physics)Geotechnical engineeringCompressibilityShear (geology)Materials scienceDirect shear testGeologyGranular materialComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract It is well-known that specimen-preparation method and the resulting sand fabric significantly affect sand behavior. In many cases, the fabric and behavior of reconstituted sand samples do not represent those of in-situ deposits. Therefore, understanding the influence of specimen preparation and sand fabric on its behavior, particularly at the critical state, is important for relating the behavior of laboratory reconstituted specimens to in-situ soil response. In this study, the effect of sand fabric and specimen-preparation method on the shearing behavior of three sands is studied using ring-shear tests. Ring-shear tests are used to reach large shear displacements and determine critical states, particularly for dense sand specimens. Moist tamping and air pluviation are used to prepare the specimens. The results indicate that the shearing behavior of sand in ring-shear tests is not only affected by the specimen-preparation method (i.e., sand fabric), but also by particle damage and compressibility. However, these mechanisms do not affect the critical states at which particle rearrangement and damage are complete and the initial sand fabric is completely erased.

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.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.495
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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