Strength improvement of high organic dredged soil by solidification/oxidization synergistic method
Bibliographic record
Abstract
Soil organic matter (SOM) has always been one of the critical factors affecting the solidification of dredged soil. This study proposes a solidification/oxidization synergistic method for treating high organic dredged soil (DS). Three solid oxidants, i.e. , sodium persulfate (PS), sodium percarbonate (PC), and potassium ferrate (PF), were added to DS in cooperation with cement, respectively. The results show that all three oxidants showed a good degradation effect on SOM and had the optimal dosage, which increased gradually with cement content (Ac) when used with cement. Under the optimal dosage of oxidant and Ac = 15%, PS and PC can improve the unconfined compression strength (UCS) of cemented DS (CDS) at 60 days of curing to nearly 4 times compared with that without oxidant, while PF can only increase the 60d-UCS to 1.5 times. In addition, the influence mechanism of different oxidants on the UCS of CDS was analyzed based on microscopic tests, proving that the three oxidants can not only degrade the SOM in CDS but also participate in the hydration reaction of cement. It is feasible to use proper amounts of PC and PS in combination with cement to solidify high organic soil.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".