Smoothness variations in early-age jointed plain concrete pavements
Bibliographic record
Abstract
This paper discusses the variations in the early-age pavement smoothness at different measurement times and locations in three jointed plain concrete pavements (JPCPs) representing different ranges of construction times. Surface profile measurements were made during the early morning and late afternoon hours at different locations of the instrumented JPCPs during the first 7 d after construction. Variations in pavement temperature during this critical period were monitored using temperature sensors installed within the test sections. The results show that measurable changes of early-age jointed plain concrete pavement (JPCP) smoothness do occur at different measurement times and locations. Within the scope of this study, it can be concluded that the variations in early-age JPCP smoothness can be significant from the standpoint of smoothness specifications. The findings of this study also indicate that morning paving produces consistent smoothness measurements when compared with afternoon paving.
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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 | 0.001 | 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".