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Record W2135513292 · doi:10.1139/cgj-2014-0334

Soil-water characteristics of compacted sandy and cemented soils with and without vegetation

2015· article· en· W2135513292 on OpenAlexvenueno aff
W. M. Yan, Guanghui Zhang

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsWettingSoil waterVegetation (pathology)Saturation (graph theory)Water retentionSoil scienceEnvironmental scienceWater contentGeotechnical engineeringPermeability (electromagnetism)Bulk densityMaterials scienceGeologyChemistryComposite material

Abstract

fetched live from OpenAlex

Experiments were undertaken to study the soil-water characteristics of compacted sandy soil (SS) and cemented soil (CS) in field and laboratory conditions. The influence of vegetation and material density on the development of negative pore-water pressure (PWP) and degree of saturation (S r ) in the studied materials was investigated. The field planting experiments demonstrated a promising survival rate of Schefflera heptaphylla in both types of material, while the (SS) promoted better growth of the seedlings than the cemented one. In the field study, PWP and S r of the compacted SS responded noticeably and promptly to natural drying–wetting cycles. However, the responses in the CS were relatively mild. When subjected to the same drying–wetting cycles, PWP responded more slowly and to a smaller magnitude compared with that of the uncemented counterpart. In addition, S r changed little in CS. An increase in the density of the SS promoted rapid development of negative PWP, while an opposite trend was observed for CS. Attempts have been made to explain the observations from the perspectives of material permeability and change in water content during a drying period in both soil types. Furthermore, in SS, the development of PWP (with a measurement limit of −90 kPa) was minimally affected by the presence of vegetation, while vegetation noticeably helped the development of negative PWP in CS. Bounds of the soil-water characteristic curve (SWCCs) of the studied materials were presented based on estimates from the drying and wetting scanning curves derived from the field monitoring. A corresponding laboratory study was carried out in an environmental chamber with controllable temperature and humidity. Monitoring results from the laboratory agreed qualitatively with those obtained from the field.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.302

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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 designObservational
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

Citations23
Published2015
Admission routes1
Has abstractyes

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