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Record W2071448495 · doi:10.1680/geng.2008.161.1.29

Loading tests on compacted soil, bottom-ash and lime layers

2008· article· en· W2071448495 on OpenAlexaff
Nilo César Consoli, Antônio Thomé, Maciel Donato, James Graham

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Geotechnical Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of Manitoba
FundersUniversidade Federal do Rio Grande do SulFundação de Amparo à Pesquisa do Estado do Rio Grande do SulConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsGeotechnical engineeringBearing capacityVoid ratioLimeSoil waterBottom ashResidualSettlement (finance)GeologyFly ashMaterials scienceSoil scienceComposite materialMetallurgy

Abstract

fetched live from OpenAlex

This paper addresses the interpretation of loading tests bearing on a layered system formed by a compacted soil, coal bottom-ash and carbide lime top-layer overlying a compressible residual soil stratum. Load–settlement behaviour is observed from tests carried out using circular steel plates ranging from 0.30 to 0.60 m diameter on the top of a 0.15–0.60 m thick artificially cemented layer. Field data demonstrate the effectiveness of compacted soil–ash–lime layers in increasing bearing capacity and reducing foundation settlements where shallow foundations are used on weak residual soils. The paper also stresses the need to express test results in terms of dimensionless variables in plots of normalised applied pressure against settlement-to-diameter ratio. The efficiency of existing analytical solutions for layered cohesive-frictional soils in determining the bearing capacity of footings on processed cemented soil overlying a weakly bonded residual soil with high void ratio is evaluated.

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)0.002
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.183
Teacher spread0.174 · 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

Citations40
Published2008
Admission routes1
Has abstractyes

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