Inversion analysis to determine design parameters for reliability assessment in pavement structures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reliability assessment has been used to evaluate the performance of pavement structures. However, probabilistic inversion analysis of pavement structure design has not yet been tested to determine the design parameters of the pavement performance function, given a specified reliability index. In this study, a limit state function numerical calculation and the inversion technique of the Nelder–Mead simplex algorithm were used to determine the design parameters for the pavement performance function. The method of moments was used to develop the forward limit state function, which was then compared to Monte Carlo simulations; the comparison indicated good agreement between the two methods. Additionally, several cases were studied to determine the design parameters of the pavement performance function for the reliability index specified in this study. The case studies indicated that the structure number significantly affected the pavement performance function.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it