Prediction of the Variation of the Resilient Modulus with Respect to the Soil Suction for Three Granular Materials Using Three Methods
Bibliographic record
Abstract
Base-course layers of a pavement structure usually are composed of granular materials which are typically in an unsaturated condition during their service life. Pavements during the last decade have been encouraged to be designed based on the mechanistic methods which use the resilient modulus (MR) as a key parameter. The soil suction has a significant influence on the MR of granular materials. In this paper, various equations proposed for predicting the MR of unsaturated granular materials from the literature are summarized. Three equations proposed for predicting the MR of granular materials summarized in this paper are selected to provide comparisons between the measured and predicted MR values of three different granular materials. The strengths and limitations of the three equations are discussed. In addition, the relationship between the MR and the soil-water characteristic curve (SWCC) is highlighted with recommendation to use it as a tool in the prediction of the MR for granular materials.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".