Analysis of Premature Low-Temperature Cracking in Three Ontario, Canada, Pavements
Bibliographic record
Abstract
An analysis of premature low-temperature cracking in three Ontario, Canada, pavements is documented and discussed. Two of the contracts consisted of a 50-mm single lift of hot-mix asphalt on recycled asphalt pavement; the third contract was a single lift overlay on a previously cracked pavement. All three pavements exhibited extensive transverse cracking during their first winter. The binders used in each of the surface courses were evaluated for possible deviations from specification requirements and for their susceptibility to cracking as a result of excessive reversible aging during cold storage. The reversible aging tendencies, as indicated by bending beam rheometer (BBR) tests after extended periods of conditioning, showed that although all three binders met the specification, they lost a considerable amount from their grade temperature as determined according to AASHTO M320 criteria. Fracture tests on the binders showed that properties in the brittle state were all considered to be poor, yet typical for unmodified materials. Fracture properties in the ductile state for the binder from the one overlay contract indicated that low resistance to ductile failure could explain the observed distress. The experience has further confirmed the need to develop an extended BBR test protocol as well as brittle and ductile fracture tests to exclude binders that will be susceptible to these types of failures for future paving contracts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".