Condition assessment of critical infrastructure with GPR
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
Tunnels, bridges and dams represent some of the most critical public infrastructure. This paper presents case studies in novel application of GPR for condition assessments of these structures. The 200st Overpass in Langley, BC, Canada case study is a successful application of multiple frequency GPR systems to assess the structural condition of a critical highway overpass along the Trans Canada corridor. The GPR survey revealed construction deficiencies including mapping subsurface voids which was necessary in order to design proper remediation. The Mission, BC, Canada case study illustrates using Pipe Penetrating Radar (PPR), the underground, inpipe application of GPR for mapping voids outside a reinforced concrete storm sewer pipe. The same void was located and confirmed from an above ground GPR survey, thus successfully combining the results of in pipe, high frequency PPR with above ground low frequency GPR surveys. A 33 inch diameter vitrified clay pipe (VCP) that experienced catastrophic failures despite being installed only seven years ago in a California municipality was the subject of the third case study. PPR and CCTV inspection of over 9,000 ft of pipe provided quantitative pipe condition data and allowed the asset owners to design the most suitable and cost effective rehabilitation and replacement strategy.
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.
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