The efficiency of laboratory test procedures for assessing field performance of concrete against Alkali-Aggregate Reaction (AAR)
Bibliographic record
Abstract
Alkali-aggregate reaction (AAR) is among the most harmful deterioration mechanisms affecting concrete infrastructure worldwide, impacting more than 50 countries. Over the last decades, numerous laboratory tests have been developed to evaluate the reactivity of aggregates and the effectiveness of supplementary cementitious materials (SCMs) to mitigate AAR. Among them, the accelerated mortar bar test (AMBT) and the concrete prism test (CPT) stand out and are used around the globe nowadays. However, in recent years, some discrepancies have been found between laboratory results (i.e., AMBT or CPT, especially AMBT) and concrete mixture performance in the field. Yet, these discrepancies have never been quantified. This work aims to critically review current laboratory methods for assessing AAR-induced development, followed by a comparison of performance (i.e., laboratory versus field) at distinct scales (i.e., laboratory specimens vs. field blocks and structures) and quantification of the risk associated with these tests to forecast AAR in the field.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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".