Structural implications and management of infrastructure assets affected by ISR: example of French experience on road bridges
Bibliographic record
Abstract
Several hundreds of bridges and civil structures in France have been recognized as affected by internal swelling reactions (ISR), some of them being critical. This comprises alkali–silica reaction cases, the number of which has been stabilized for more than 30 years through recommendations having now gained the status of standards, and delayed ettringite formation-affected massive structures or precast elements, still in an increasing number. Management of the ISR-affected road bridges has deserved guidelines published in 2003, which have proven effective until now with limited updates. For optimal maintenance funds allocation, priorities in investigations for diagnosis have been précised. First actions have to be based on cracking index and overall deformation surveys, leading to subsequent bridge state rating. Then, monitoring requirements, as well as numerical reassessment needs and methods have been clarified. Experience in mitigating and repair techniques has been collected. Reliability in prognosis still deserves research efforts which are detailed in this paper.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".