Long-term behaviour model of skid resistance for asphalt roadway surfaces
Bibliographic record
Abstract
Skid resistance (SR) is relevant to road safety. Several researchers have showed that SR diminishes its value over time depending on the traffic-aggregated interactions, and the presence of heavy vehicles in the traffic stream. The classical SR model shows that its value drops from a starting value to an equilibrium value over time. However, this behaviour in low-volume roads is not entirely true. In this paper, an SR model in a single mathematic specification is proposed, which considers the polishing effect of heavy traffic through the polishing equivalence factor. The model was calibrated by using data measured with a SCRIM device from 1100 test sections in Chile. Considering speed and temperature factors calibrated for Chile, data were processed and corrected. It was concluded that the model for long-term behaviour of SR is satisfactory, but it is necessary to include the seasonal effects for a more realistic model.
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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".