Concrete damage due to oxidation of pyrrhotite-bearing aggregate: a review
Bibliographic record
Abstract
Oxidation of pyrrhotite-bearing aggregates is one of the major causes of concrete damage in numerous buildings in Trois-Rivières in Canada and Connecticut in the USA. In the presence of moisture and oxygen, pyrrhotite oxidizes to generate iron-and sulfate-rich secondary minerals that cause internal sulfate attack. Iron sulfides are accessory minerals of different rock types. The distribution of sulfides is often very heterogeneous in terms of aggregate particles, even at the level of the quarries in which some areas may contain copious amounts than others, which complicates the sampling method. Pyrrhotite is a complex mineral with varying chemical composition, crystallographic structure, and specific surface area. These factors influence the reactivity of pyrrhotite. Therefore, it is challenging to control the quality of the aggregate sources. In this study, recent advances in the identification and quantification of pyrrhotite to diagnose complicated cases are presented, and a performance-based approach for the quality control of new sources of aggregates is introduced. The performance-based approach is preferred because it eliminates the influence of the oxidation of pyrrhotite.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".