Bibliographic record
Abstract
Tire/pavement noise has become a major factor in the choice of the pavement for the decision maker of the Quebec department of transportation. A literature review was done to understand the tire/pavement noise generation mechanism and to identify the methods, both in laboratories and in the field, currently use to measure the tire/pavement noise. To rank Quebec's usual pavement by their noise level, 19 different sections were tested with a CPX noise trailer. Texture was also measured on the same sections. The results have shown that the PCC sections are not noisier or quieter than the HMA sections. A good correlation was found between texture and noise level for the PCC sections; the higher the texture, the higher the noise level. For the oldest HMA sections studied, the same relation was found. However, for the HMA surface treatment sections, there was also a good correlation, but this time the noise level decreases when the texture increases. For the HMA mixes, the noise level increase when the percent passing the 5mm sieve increases. This suggests that limiting the percent passing on the 5mm sieve might be a way to reduce the noise level on the HMA sections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".