The Selection of PCC Joint Repair Trigger Values and Void Detection for Concrete Pavements Overlaid with Asphalt
Bibliographic record
Abstract
This study reports the results of deflection testing aimed to establish appropriate performance threshold values and evaluate the effect of asphalt concrete overlays (ACOs) on measured deflections and void detection. Rehabilitation planning can be improved through timely joint repairs and detecting voids more accurately. Collected deflections were correlated with load transfer efficiencies at varying confidence intervals to select performance threshold values. Moreover, testing was performed on joints prior to and after ACO milling to evaluate its effect on measured deflections and void detection. Deflection correction factors for each load level are recommended to calibrate deflections to account for the presence of ACOs and to improve void detection analysis. Presented recommendations can improve rehabilitation planning by applying trigger values appropriate to local pavement structures and climate and by accounting for the contribution of ACOs on slab deflections and void detection analysis, without the need to mill ACOs prior to FWD testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".