Ten-year field evaluation of corrosion-inhibiting systems in concrete bridges barrier walls
Bibliographic record
Abstract
The performance of eight commercial corrosion-inhibiting systems was assessed in the field over ten years on reinforced concrete barrier walls of a highway bridge that was subjected to severe environmental conditions. These systems were composed of one or more of the following components: anticorrosion concrete admixtures, reinforcement coatings, and concrete surface coatings/sealers. The field evaluation consisted of annual surveys of corrosion potential and corrosion rate, as well as visual inspections and testing of concrete cores. After ten years, the main reinforcement of the barrier walls, at a depth of 75 mm [3 in.], was found in relatively good condition due to an initially good quality concrete. Special bars embedded at a depth of 13 mm [1/2 in.] in the barrier walls showed signs of advanced corrosion for all systems, however, no visible signs of corrosion were found on 25 mm [1 in.] deep bars. Non-destructive corrosion evaluation over the 25 mm [1 in.] deep ladder rebars indicated that the system containing the inorganic anticorrosion admixture provided consistently lower risks of corrosion, followed by systems containing organic anticorrosion admixtures, in comparison to the control system and other systems. The low concrete permeability and different stability of the protective layer forming on the bars may explain the observed differences in the effectiveness of these systems.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".