Method for Analyzing Time-Series GPR Data of Concrete Bridge Decks
Why this work is in the frame
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Bibliographic record
Abstract
Ground-penetrating radar (GPR) has been extensively studied in North America as a nondestructive evaluation (NDE) technology for inspection of concrete bridge decks. With current practices, however, GPR has only proven to be an indicator of potential damage. Basically, to obtain the condition map for a concrete bridge deck, one would try to analyze one-time GPR data based mostly on the relative difference between reflection amplitudes at the top rebar layer. With a hypothesis that time-series GPR data can provide better information on bridge deck deterioration progression, this study investigates and proposes a new method to interpret those time-series data sets. Based on a correlation coefficient between A-scans, the proposed methodology was implemented and validated for a bare concrete bridge deck in New Jersey. The map provided by the proposed method clearly shows deterioration progression between the two consecutive scans, whereas the traditional analysis technique using the top rebar amplitude suggests unreasonable improvement of the deck condition over time.
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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 | 0.001 | 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