A study on pothole repair in Canada through questionnaire survey and laboratory evaluation of patching materials
Bibliographic record
Abstract
To investigate the current pothole repair practices in Canada, a questionnaire was distributed to Canadian transportation agencies. Outcomes showed a large portion of pothole repairs were performed during the summer season. Conventional cold mix, hot mix asphalt, Quality Pavement Repair, and Innovative Asphalt Repair were identified as commonly used patching materials. Moreover, the ‘throw-and-go’ method was the most common patching procedure and durability of repaired patches in winter was significantly less than repaired patches in summer. To evaluate the performance of patching materials, a laboratory testing program was conducted on cold mixes identified by the survey as being most commonly used. The laboratory results showed that curing time and temperature had a significant effect on strength gain for all cold mixes. Conventional cold mix showed higher stability and cohesion properties, while Quality Pavement Repair showed better moisture resistance and adhesion properties. All the cold mixes were sensitive to freeze–thaw damage.
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 | 0.002 | 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".