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Record W2079010156 · doi:10.1520/gtj11431

A Physical Model for Sloping Capillary Barriers

2004· article· en· W2079010156 on OpenAlexaff
Denny Tami, Harianto Rahardjo, DG Fredlund

Bibliographic record

VenueGeotechnical Testing Journal · 2004
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCapillary actionReflectometryCapillary pressureGeotechnical engineeringInstrumentation (computer programming)Pore water pressureMaterials scienceSoil waterEnvironmental scienceSoil scienceGeologyTime domainPorosityPorous mediumComposite material

Abstract

fetched live from OpenAlex

Abstract A physical capillary barrier model has been developed to study the mechanism and the effectiveness of a capillary barrier for slope stabilization purposes. A sloping two-layer capillary barrier model consisting of a relatively fine soil layer over a relatively coarse soil layer was constructed inside a specially designed apparatus. Simulated rainfalls of different intensities and durations representative of tropical climatic conditions were applied through a rainfall simulator. Various instruments consisting of tensiometers for pore-water pressure measurement, time domain reflectometry (TDR) for water content measurement, magnetic flow meter and electronic weight balances for water balance measurements were used in the experiment. The results obtained from various types of instrumentation were in good agreement. The experimental results show that the performance of the capillary barrier under the influence of a high precipitation rate is primarily governed by the storage capacity of the relatively fine soil of the capillary barrier.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.026
GPT teacher head0.242
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 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

Citations70
Published2004
Admission routes1
Has abstractyes

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