Remote Monitoring of a Rehabilitated Concrete
Bibliographic record
Abstract
As part of a major rehabilitation project, embedded instrumentation was installed in a concrete bridge barrier wall to remotely monitor the key physico-chemical parameters influenced by the prevailing environmental conditions. The remote monitoring was part of a broader experimental program, in which different rehabilitation techniques used in the reconstruction of a bridge barrier wall were evaluated in the field and in the laboratory. The barrier wall was instrumented in 1996 with over a hundred embedded sensors for the measurement of temperature, relative humidity, electrochemical potential and longitudinal strain. The data was collected on an hourly basis with 5 data loggers equipped with cellular modems for data transmission. The bridge structure located near Montreal (Quebec) has experienced typical Canadian temperature extremes from-25C in the winter to +30C in the summer, several wet-dry and freeze-thaw cycles, as well as severe restrained shrinkage cracking in the new barrier wall at earlyage. The paper presents data obtained from five years of remote monitoring of a bridge under harsh climatic conditions. The full evaluation of the long-term performance of the rehabilitation techniques based on corrosion surveys and testing conducted on-site and in the laboratory will be part of a separate paper.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".