Seasonal and Temperature Adjustment Models of Pavement Properties from Seismic Nondestructive Evaluation
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
New Jersey Department of Transportation (NJDOT) initiated a study with an objective to calibrate the AASHTO seasonal and temperature adjustment models, or to develop new ones that will take into consideration New Jersey specific environmental conditions. To achieve the objective, twenty-four pavement sections were instrumented to monitor pavement temperature and moisture, frost/heave penetration depth, rainfall and air temperature. A nondestructive testing (NDT) program was conducted on these sections for a period of two years. Seismic Pavement Analyzer (SPA) and Falling Weigh Deflectometer (FWD) were used to evaluate the pavement structural response and pavement properties (elastic moduli) on a monthly basis. From the collected environmental and NDT data, temperature and seasonal models were developed through statistical analyses, such as analysis of variance (ANOVA) and regression analysis. The scope of the project is presented and pavement evaluations using SPA are discussed. Correlation of pavement layer moduli to environmental variables from three seismic tests: Ultrasonic Surface Wave (USW), Impulse Response (IR), and Spectral Analysis of Surface Waves (SASW) are presented and observed trends are discussed.
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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 | 0.000 | 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 | 0.000 |
| 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