Stabilisation and solidification of contaminated soil and waste: Practice
Bibliographic record
Abstract
Stabilisation/Solidification of Contaminated Soil and Waste comprises 2 handbooks designed to provide students, practitioners, site owners, and regulators with authoritative guidance to the science underpinning this versatile remedial technology, and how it is applied in real-world situations. \n \nStabilisation/Solidification (S/S) uses readily available cementitious binders to turn contaminated soil and waste into a rock-like product that reduces the risk to public health and the environment. S/S has been employed at hundreds of sites in the USA, Canada, and Europe to improve the physical and/or chemical properties of contaminated soil and waste to enable development to take place or to safely manage a source of pollution. \n \nPractice: describes how S/S is designed and implemented, including discussions on risk reduction, the development of performance specifications, available binders, treatability studies, in-situ and ex-situ equipment/operations, quality assurance, capping, site closure including long term monitoring strategies. The extensive appendices include a list of over 200 completed S/S remediations and over 40 case studies.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.023 |
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".