Assessment of the quality of full-depth reclamation (FDR) using a dynamic cone penetrometer (DCP): a case study
Bibliographic record
Abstract
The full-depth reclamation with no stabilization (FDR-NS) is widely used as a pavement rehabilitation technique. It is important to evaluate the on-site characteristics of FDR-NS materials to avoid short-term underperformance. The need for performance-based testing could then be supported by in situ and non-destructive testing, such as dynamic cone penetrometer (DCP). DCP allows to estimate the bearing capacity of the pavement structure and to verify its homogeneity according to the depth. The objective of this research is to evaluate the applicability of using DCP to assess the quality of FDR-NS. Overall, DCP results showed a good reliability, allows to measure the effective depth of reclamation and to observe a significant reduction (average of 75%), in terms of DCP values, between before and after the reclamation (FDR) process. Thus, the potential of using DCP for FDR-NS rehabilitation was confirmed. The results from this research provide a rational basis for establishing specifications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".