Relating concrete pavement noise and friction to three-dimensional texture parameters
Why this work is in the frame
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Bibliographic record
Abstract
The objectives of this research were to characterise concrete pavement surface texture using three-dimensional (3D) surface texture indicators, to explore the relationship between pavement noise/friction and texture parameters. A newly constructed Portland cement concrete pavement with 13 types of textures was selected as test site. Pavement texture heights were recovered using photometric stereo technique. A comparative study was conducted between proposed 3D texture parameters and other established two-dimensional texture measurements, i.e. the circular track meter and the high-speed texture profiler. Correlation analysis between 3D texture parameters and noise/friction data were also carried out to explore relationship between pavement texture and noise/friction. In addition to texture amplitude, the direction and distribution of pavement texture have strong impacts on pavement noise and friction. It is possible to have a better understanding of surface texture and pavement noise/friction using combinations of the proposed 3D texture parameters.
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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 | 0.001 | 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 it