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Record W2088015855 · doi:10.1139/t03-047

Influence of mineralogy on swelling and consolidation of soils in eastern Saudi Arabia

2003· article· en· W2088015855 on OpenAlexfundvenueno aff
Shahid Azam

Bibliographic record

VenueCanadian Geotechnical Journal · 2003
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersKing Fahd University of Petroleum and MineralsUniversity of Alberta
KeywordsExpansive clayAnhydriteConsolidation (business)GypsumGeologySoil waterGeotechnical engineeringClay mineralsSwellingAtterberg limitsMineralogyMining engineeringSoil scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The mineral calcium sulphate transforms from anhydrite through bassanite to gypsum and then can convert back to bassanite and anhydrite. This transformation of calcium sulphate causes volume change that adds to the potential hazards with indigenous soils containing expansive clay minerals. Heave and settlement are the most important geotechnical problems associated with many argillaceous soils in eastern Saudi Arabia. Mineralogical evolution and engineering behaviour of such soils are governed by local geology and severe climatic and environmental conditions prevalent in the region. Based on laboratory investigations, this paper discusses the influence of mineralogy on swelling and consolidation of expansive clay, calcium sulphate forms, and their mixtures. Mineralogy is investigated using geotechnical index properties and thermal and X-ray diffraction analyses. Swelling and consolidation characteristics are directly determined and are studied in conjunction with microstructural assessment. Results indicate that under the hot and humid climate prevalent in eastern Saudi Arabia, form changes in calcium sulphate can take place in the time frame of engineering importance. The volume-change behaviour of local expansive clay depends on the form and amount of calcium sulphate present in the soil.Key words: calcium sulphate, expansive clay, swelling, consolidation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.286

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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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

Citations71
Published2003
Admission routes2
Has abstractyes

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