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Record W2024899951 · doi:10.1139/t06-090

Drying and wetting characteristics of a two-layer soil column

2007· article· en· W2024899951 on OpenAlexvenueno aff
I Gde Budi Indrawan, Harianto Rahardjo, Eng‐Choon Leong

Bibliographic record

VenueCanadian Geotechnical Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersJapan International Cooperation AgencyNanyang Technological University
KeywordsInfiltration (HVAC)Geotechnical engineeringWettingPermeability (electromagnetism)Water contentWater flowGeologySoil scienceSoil waterWater retention curvePore water pressureMaterials scienceComposite materialField capacityChemistry

Abstract

fetched live from OpenAlex

The drying and wetting characteristics of a two-layer soil column consisting of a 50 cm thick soil mixture over a 50 cm thick gravelly sand were investigated in this study. A series of infiltration tests were conducted in the laboratory through an infiltration column apparatus equipped with a tensiometer–transducer system, time-domain reflectometry, and water flow measurement system. Numerical analyses were performed using a finite element model to simulate water infiltration into the laboratory model under steady-state and transient conditions. The experimental data and numerical simulation results showed that static nonequilibrium profiles of pore-water pressure head were developed in the gravelly sand shortly after a drying process was started. The low unsaturated permeability of the gravelly sand resulted in a delay in downward water flow into the lower soil layer during a wetting process portion of the rainfall test.Key words: drying and wetting characteristics, soil column, infiltration, numerical analyses, soil-water characteristic curve, permeability function.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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
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

Citations31
Published2007
Admission routes1
Has abstractyes

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