Development of a multi-modal overlay tester for the evaluation of asphalt overlay cracking behaviors
Bibliographic record
Abstract
Reflection cracking is a critical issue in asphalt overlay pavement. Temperature variation and traffic loading are the main fracture modes acting on the material. In this paper, a multi-modal overlay tester is proposed for the evaluation of the reflection cracking resistance of an asphalt mixture, an approach that simulates three loading modes on asphalt specimens. A fine dense-grade hot mix asphalt is used as the test specimen and subjected to different loading conditions such as single Mode I, II, and III loading simulations and combined I+II and I+II+III loading simulations. Results show coefficients of variation (CVs) of 2.5%, 10.3%, and 7.4% for the Mode I, II, and III loading simulations, respectively. Furthermore, the β coefficient, with a CV of 7%, is used to represent the crack resistance of the asphalt mixture. Finally, the crack propagation occurs rapidly when subjected to tension and lateral displacement prior to repeated traffic loading simulations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".