Developing Pavement Design Inputs for Fine-Grained Subgrade Soils in Manitoba
Bibliographic record
Abstract
Resilient modulus is the primary design input for subgrade soil in the Mechanistic-Empirical Pavement Design Guide (MEPDG). Characterization of subgrade resilient modulus requires instrumentation and technical experience that are not available in many soil testing Laboratories. The objective of this paper is to characterize the resilient modulus of typical subgrade soils available in Manitoba and develop design inputs for the MEPDG. The resilient modulus of fine-grained subgrade soil samples was tested at different levels of moisture content. Results of the laboratory testing were used to develop prediction models for resilient modulus as function of physical properties of the subgrade soil and stress state. A good agreement was found between measured resilient modulus and predicted values with the proposed models. The proposed models were compared to those developed under the Long Term Pavement Performance (LTPP) program. The results showed that the proposed models provided more reliable predictions with lower root mean square error.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".