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Record W2121519501 · doi:10.1186/s40068-014-0019-5

A two stage model for moisture-induced deformations in expansive soils

2014· article· en· W2121519501 on OpenAlexaff
Maki Ito, Shahid Azam, Yafei Hu

Bibliographic record

VenueENVIRONMENTAL SYSTEMS RESEARCH · 2014
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsGeotechnical engineeringSoil waterExpansive claySaturation (graph theory)Water contentSuctionInfiltration (HVAC)MoistureOverburden pressureSoil scienceEnvironmental scienceOverburdenGeologyMeteorologyMathematics

Abstract

fetched live from OpenAlex

Abstract Background Moisture-induced suction changes in expansive soils due to infiltration and evaporation result in failure of civil infrastructure. The objective of this paper was to develop a two stage deformation model by simultaneously calculating soil suction and stress state. The model predictions were validated using a one-year field monitoring data. Results Deformations in expansive soils closely match cyclical suction changes corresponding to seasonal weather variations. Volume changes fluctuated close to the ground surface and gradually decreased with depth (overburden pressure) due to isolation from meteorological effects. The top 2 m depth was found to be the active zone susceptible to moisture variations. Conclusions The model agreed well with the monitoring data trends with deviations attributed to analytical assumptions in the equations, ineffective capture of antecedent soil conditions, possible soil heterogeneity and anisotropy, and hysteresis in soil saturation and desaturation.

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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.297
Teacher spread0.252 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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