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Record W2122995257 · doi:10.1139/cgj-2012-0347

Measuring soil pressure within a soil mass

2013· article· en· W2122995257 on OpenAlexvenueno aff
Mark Talesnick

Bibliographic record

VenueCanadian Geotechnical Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringStiffnessLateral earth pressureOverburden pressureHysteresisSoil waterNonlinear systemStress (linguistics)Particle (ecology)Soil typeSoil scienceSoil mechanicsEnvironmental scienceGeologyEngineeringStructural engineeringPhysics

Abstract

fetched live from OpenAlex

Reliable measurement of pressure within a particulate media has frustrated researchers in the field of soil mechanics and soil structure interaction for many years. The difficulty stems from the fact that most sensing systems involve compliance in the measurement concept. This compliance imparts a parasitic output to the measurement. In the past, researchers have attempted to calibrate this disturbance. Research has demonstrated that calibrations of this sort are dependent upon soil type, particle size, sensor geometry, and soil stiffness. Response of such sensors has been shown to be stress history–dependent: the response upon unloading may be highly nonlinear, resulting in a high degree of hysteresis. Complications in the measurement of soil pressure within a soil mass are significantly more complex from those met in the measurement of soil pressure at a structural boundary and must be considered separately. This paper utilizes a concept called the Null Soil Pressure System. Null pressure sensors were embedded and tested in a series of uniformly graded soils with particle diameters ranging from less than 0.15 to 15 mm. The data indicates that the response of the null pressure sensor consistently exceeds the actual soil pressure by a value of 4% ± 3%. This outcome is seen to be independent of soil type, particle size, stiffness, and stress history. No hysteresis is noted between loading and unloading, and additional loading cycles align with that of the virgin loading segment.

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 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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.012
GPT teacher head0.173
Teacher spread0.161 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations62
Published2013
Admission routes1
Has abstractyes

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