THE MICRO-DEVAL ABRASION TEST FOR COARSE AND FINE AGGREGATE IN ASPHALT PAVEMENT
Bibliographic record
Abstract
Aggregates used in asphalt pavement must be strong and long lasting to withstand processing, hauling, placement, traffic loading and weathering. The abrasion resistance and durability of aggregates for use in asphalt pavement may be evaluated using the micro-Deval abrasion test. In Ontario, development of the micro-Deval test was driven by the need for a simple, inexpensive and precise test to evaluate mechanical strength when wet, predict performance of aggregate, and have a demonstrated correlation with field performance. The micro-Deval test is compared to other test methods used to evaluate abrasion and wear. Since 1992, a number of Canadian provinces have introduced the micro-Deval abrasion test into their aggregate specifications. The micro-Deval test can be used to assess the quality of coarse and fine aggregate for use in hot-mix asphalt. It is a reliable predictor of mechanical breakdown of coarse aggregate and of the amount of weak, soft particles in sand.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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".