Assessing Spring Load Restrictions Using Climate Change and Mechanistic-Empirical Distress Models
Bibliographic record
Abstract
During the spring, as the average daily air temperature and declination of the sun increases, so does the temperature of the asphalt surface layer. As the increase in temperature travels through the surface layer and reaches the unbound aggregate base layer, the saturated base layer begins to thaw. For a flexible pavement with a fine-grained subgrade, the moisture in the base becomes trapped between the impermeable asphalt concrete layer and the frozen, fine-grained subgrade. The excess water requires a long period of time to properly drain. During this period, the subgrade becomes considerably softer and decreases in stiffness, and the roadway experiences an increase in damage and reduction in service life. The duration of thaw for a typical pavement structure depends on soil type, moisture and thermal properties, air temperature, solar radiation, drainage and the location of the site. Spring load restrictions are applied to protect weak pavement structures that would otherwise experience excessive deflections. Nearly 58 % of the Manitoba Provincial pavement network is subjected to spring load restrictions, and most of these roads consist of a thin flexible pavement or an asphalt surface treatment. This paper relates pavement deflection data from FWD testing to environmental indices such as the thaw index. Deflection data collected since 1990 on pavement sections and the LTPP site in Manitoba are used to establish
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".