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Record W2515185468 · doi:10.5539/jgg.v8n3p42

Geotechnical and Chemical Evaluation of Tropical Red Soils in a Deltaic Environment: Implications for Road Construction

2016· article· en· W2515185468 on OpenAlexvenueno aff
Akaha Celestine Tse, Adunola O. Ogunyemi

Bibliographic record

VenueJournal of Geography and Geology · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsAtterberg limitsSoil waterGeotechnical engineeringCalifornia bearing ratioSubgradeRed soilGeologyWater contentSpecific gravityEnvironmental scienceSoil scienceMineralogy

Abstract

fetched live from OpenAlex

Tropical red soils which occur in the dry flatlands and plains of the eastern Niger Delta Nigeria were evaluated using combined conventional engineering geological investigation with major oxide geochemistry to determine their properties and evaluate their engineering performance in road construction. Laboratory test results indicate that the brownish materials are uniformly graded, silty clayey sandy soils. The silica to sesquoxide ratio values of 3 to 4.37 indicate that they are non-lateritic tropically weathered soils. The average values of the specific gravity, liquid limit, plasticity index and shrinkage limits are 2.67, 37%, 10% and 7.6% respectively. They are soils of low to medium plasticity. The unsoaked and soaked CBR values range from 14-38% and 3-9% respectively whereas the average undrained shear strength is 172kN/m2. Maximum dry density and optimum moisture content values fall between 1680 to 1880kN/m2 and 13-16% respectively. Generally the soils classify as A-7-6 to A-2-4 subgroups of the AASHO classification. The overall implication of these composite engineering properties is that the non-lateritic soils rate as poor to fair subgrade materials.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.221
Teacher spread0.211 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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