Variations in Backcalculated Pavement Layer Moduli in LTPP Seasonal Monitoring Sites
Bibliographic record
Abstract
Seasonal variations in structural parameters were calculated from Falling Weight Deflectometer data on 25 LTPP flexible seasonal monitoring sections. In all, 23,976 deflection basins were analyzed. The deflection basins were collected monthly between the fall of 1993 and the spring of 1995. The test locations were distributed around North America from Saskatchewan to South Texas and from Idaho to Maine. The sections all consisted of asphalt surfacing and granular bases (and some granular subbases) over subgrades. Asphalt thicknesses ranged from 46 to 277#mm. Seasonal variations observed on selected sections in this database and documented in this paper include variations in asphaltic materials with temperature, variations in moduli of the unbound materials with precipitation, and variations in moduli of unbound materials due to freeze/thaw. For moderately thick to thick asphalt sections (>125 mm) the temperature dependency can clearly be seen in the deflection basins. As expected, this variation in deflections, and AC modulus is sinusoidal over the year. The amplitude of the sinusoidal variations were found to be heavily influenced by the thickness of the AC layer. Thicker AC sections exhibited higher sinusoidal variations. Base and subgrade values tended to be influenced by temperature but remained more consistent throughout the year except in cases where freeze̸thaw effects were seen. During freeze conditions, the moduli of the unbound (base and subgrade) layers drastically increased.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".