Compressive Strength Gain Behavior and Prediction of Cement-Stabilized Macadam at Low Temperature Curing
Bibliographic record
Abstract
For cement-based materials, the curing temperature determines the strength gain rate and the value of compressive strength. In this paper, the 5% cement-stabilized macadam mixture is used. Three indoor controlled temperature curing and one outdoor natural curing scenarios are designed and implemented to study the strength development scenario law of compressive strength, and they are standard temperature curing (20°C), constant low temperature curing (10°C), day interaction temperature curing (varying from 6°C to 16°C), and one outdoor natural temperature curing (in which the air temperature ranges from 4°C to 20°C). Finally, based on the maturity method, the maturity-strength estimation model is obtained by using and analyzing the data collected from the indoor tests. The model is proved with high accuracy based on the validated results obtained from the data of outdoor tests. This research provides technical support for the construction of cement-stabilized macadam in regions with low temperature, which is beneficial in the construction process and quality control.
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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 | 0.000 | 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) | 0.001 | 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".