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Record W2567658889 · doi:10.1520/gtj20150181

Adaptation of Broadband Simple Shear Device for Constant Volume and Stress-Controlled Testing

2016· article· en· W2567658889 on OpenAlexaff
Ali Shafiee, Jonathan P. Stewart, Rupa Venugopal, Scott J. Brandenberg

Bibliographic record

VenueGeotechnical Testing Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsOpal-Rt Technologies (Canada)
Fundersnot available
KeywordsGeotechnical engineeringSimple shearShear stressAdaptation (eye)Constant (computer programming)Shear (geology)Materials scienceStress (linguistics)Simple (philosophy)GeologyStructural engineeringEngineeringComputer scienceComposite materialPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract We adapted an existing digitally controlled simple shear device, originally designed for drained testing with strain-control, to perform constant height testing under strain- or stress-controlled conditions. The re-designed system provided PID control of horizontal displacements or loads coupled with either vertical force or displacement control (for drained and constant-volume testing, respectively). The new system had substantially similar horizontal displacement control capabilities as the previous system. The tracking error under stress-controlled loading depends on amplitude and frequency of the load; however, its value was almost the same as errors in strain-controlled tests for common shear strain/stress amplitudes. High-precision vertical control was achieved during constant height testing in two respects: (1) height change was small (less than 0.05 % of the specimen height for large shear-strain tests), even at high frequencies; and (2) top cap rocking was small, with the vertical displacements due to rocking at the specimen edge being half or less than average changes in specimen height.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.239
Teacher spread0.208 · 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
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

Citations7
Published2016
Admission routes1
Has abstractyes

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