PC-based and MgO-based binders stabilised/solidified heavy metal-contaminated model soil: strength and heavy metal speciation in early stage
Bibliographic record
Abstract
An investigation into using Portland cement (PC)-based and magnesia (MgO)-based binders for treating contaminated model soil was carried out to study the benefit of novel binders over conventional ones in stabilisation/solidification systems (S/S), as well as the binding mechanism involved. Binders used in this study include PC, ground granulated blast-furnace slag, pulverised fly ash and magnesia. The strength and the leaching properties of S/S treated samples by way of unconfined compressive strength and sequential extraction tests are presented. The results show that the early-age strength of these mixes is influenced by the reactivity of binders; heavy metals were principally distributed in the carbonate and the iron/manganese (Fe/Mn) oxide fractions in all mixes after 28 days of curing time; the speciation distribution characteristics are not the same among zinc (Zn), copper (Cu), nickel (Ni) and lead (Pb), and the stability of Zn, Cu, Ni and Pb benefits from a longer curing time and the use of magnesia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".