Characterisation of Geotechnical Properties of Residual Tropical Soils Used for Road Infrastructure: French Guiana Experience
Bibliographic record
Abstract
This paper presents the first laboratory study of four materials (three lateritic soils and one sandy soil) mainly used in road construction in French Guiana. The analysis of macroscopic behaviour by physical tests, following French standards, made it possible to classify and group the samples with respect to the rules specified in the Guide des Terrassements Routiers (GTR). According to the GTR, these raw materials could only be used as backfill materials and under very specific hydric conditions. Chemical and mineralogical characterisation by the X-ray fluorescence analysis, scanning electron microscopy observation supplemented by the X-ray microanalysis, and the infrared analysis revealed differences in the main minerals. Indeed, the presence of mineral species such as kaolinite and gibbsite and oxides such as goethite and hematite was detected. The macroscopic and microscopic characteristics of the four soils made it possible to establish a relationship between their geotechnical and mineralogical properties. Finally, the results of this study led to the conclusion that the mineralogical composition and geotechnical properties of lateritic soils must be known simultaneously to allow correct identification for their application in road construction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".