The Effect of Mineral Powder on the Surface/Interface of Aggregates and Asphalt
Bibliographic record
Abstract
This paper attempts to analyze the effect of mineral powder on the adhesion of aggregates and asphalt. First, it employs the gravimetric method to quantitatively analyze the peeling rate of asphalt and asphalt mortar from the surface of basalt, andesite, and limestone aggregates. Then, it takes microscopic pictures of the mineral powder adhered on the surface of the aggregates to observe the distribution of mineral powder in the asphalt mixtures, and uses profiles to analyze the adhesion status of mineral powder on the surface of the aggregates. At last, this paper analyzes the effect of mineral powder particles on the surface/interface of the aggregates and asphalt, and the results indicate that mineral powder has increased the roughness of the surface of the aggregates, therefore it indirectly promotes the adhesion of asphalt on the surface of the aggregates; the mineral powder particles interact with the surface texture of the aggregates, forming an embedding and wedging structure in the texture; compared with aggregates with smooth surface, the adhesion promotion effect is stronger.
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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 | 0.001 | 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 | 0.001 |
| 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".