The pyrite heave problem: new insights from trace-element analysis
Bibliographic record
Abstract
Over 12 000 houses built in Ireland between 2002 and 2008 are estimated to have sustained structural damage due to swelling initiated by pyrite in crushed rock aggregate beneath floor slabs. The Irish Standard I.S. 398-1 presented a categorization protocol for sub-floor fill material suspected of causing pyritic expansion. While at the extremes, the current risk characterisation protocol is definitive, there is a broad range of conditions where the findings are inconclusive, and the risk assessment requires expert interpretation. In this study, the possibility of using trace-element analysis to better quantify risk from reactive pyrite has been explored. The form and amount of pyrite in sedimentary rock are determined by the depositional environment, which also determined the concentration of trace elements such as molybdenum (Mo) and uranium (U). In this study, a range of high- and low-risk aggregates has been analysed. The results show very good correlation between the empirically derived risk for pyrite expansion categories and molybdenum and uranium enrichments and the ratio between these concentrations. The results to date are very promising and suggest that further research and testing of more samples will help to confirm the basis of the analysis and establish numerical risk thresholds.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".