Field investigation of granular base rehabilitation project incorporating a woven geotextile separation layer, sand, and cement stabilization
Bibliographic record
Abstract
Full-depth reclamation and cement strengthening has been used successfully to dry and strengthen granular pavements. However, some thin pavements fail due to severe wetting-up of the subgrade, thus requiring additional substructure strengthening and (or) drainage systems. This research investigated the laboratory characterization and in situ field mechanical behaviour of full-depth reclaimed and cement-stabilized granular materials in conjunction with a woven geotextile and sand drainage system. This research showed that the integration of cement-stabilized reclaimed granular materials with a geotextile separation layer and sand drainage system significantly improved the mechanical primary response and climatic durability properties of the reclaimed road structure. The cement-stabilized and geotextile separation–drainage system improved the structural asset management test results from a completely failed road structure to primary plus load-carrying capacity. This research also demonstrated an improved correlation between the mechanistic material constitutive properties of the stabilized aggregate to the end-product field structural assessment relative to conventional California bearing ratio and unconfined compressive strength test results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".