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Record W7083582621 · doi:10.1016/j.geoai.2025.100039

Expansive soil characterization: CC/CS ratio method

2025· article· en· W7083582621 on OpenAlexaboutno aff

Bibliographic record

VenueGeodata and AI. · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsOedometer testExpansive claySwellingExpansiveClay soilShrinkageSoil water

Abstract

fetched live from OpenAlex

This paper suggests a new method for characterizing expansive soils by considering recorded data from oedometer test, namely compression index (C C ), swelling index (C S ) and the swelling pressure (σ S ). Collected data included recorded values of the three parameters from 168 Tunisian soil samples and 41 soil samples from Algeria, Canada, France, Morocco and USA. Main finding was that when the C C /C S ratio is greater than 10, the soil is classified non-expansive with a swelling pressure lesser than 50 kPa. In turn, when C C /C S < 10, the soil is classified as expansive with a swelling pressure higher than 50 kPa when its clay content is above 35%. Whilst, for sand clays with clay content less than 30%, the swelling pressure is lower than 50 kPa despite the C C /C S ratio is lower than 10. For the classified Tunisian expansive soils, the cloud dots in (C C /C S ; σ S ) plan is bounded between two parallel lines, thus suggesting the primary correlation based on the proposed method of characterization of expansive soils.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.247
Teacher spread0.237 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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