Evaluation of corrosion of reinforcement in repaired concrete
Bibliographic record
Abstract
Corrosion of steel in concrete is a complex phenomenon affected by many environmental factors. A reliable and effective non-destructive approach for assessing and predicting the state of reinforcement corrosion in concrete has not yet been developed. Current methods do not account for the effects of prevailing environmental conditions. Half-cell potential, linear polarization and concrete resistivity measurements are sensitive to the ambient environment, especially oxygen and water in concrete. Completely water-saturated concrete, for instance, can lead to oxygen starvation, resulting in corrosion potential and current values that are lower than normally expected and provide, therefore, a poor prediction of the corrosion state. This paper presents the results of a study of the reinforcement corrosion in repaired concrete slabs taken from an old bridge in Hawkesbury, Ontario and additional results measured on electrochemical cells. Each corrosion measurement technique has its specific characteristics and limitations. The investigation showed that a better and more reliable prediction could be obtained by analyzing the data from above measurements jointly by considering the effects of environmental conditions.
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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 | 0.000 | 0.001 |
| 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 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".