Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A case study for the reclamation of a slurry pond as part of an offshore reclamation project in Singapore is presented in this paper. The slurry pond covered an area of 180 ha. The slurry in the pond was recently deposited ultra-soft high-plasticity clay. The water content of the slurry was more than 120% and the undrained shear strength was less than 8 kPa. The reclamation was first carried out by spreading sand fill in thin layers 20 cm thick using a specially designed sand spreader. The filling speed was carefully controlled to allow the slurry to be consolidated before more fill could be placed. Despite the precautions a failure occurred, in the form of mud bursting. As a remedial measure, geotextile sheets were used to cover a total area of 630 000 m2 before more sand fill was placed. After the completion of fill placement, fill surcharge and prefabricated vertical drains (PVDs) were used to improve and accelerate the consolidation of the slurry. As the performance of PVDs would deteriorate after they had undergone large deformation, they were installed in two passes. In the first pass PVDs were inserted with a square grid spacing of 2·0 m. After nearly 1·5 m of settlement had taken place, the second pass of PVDs with the same spacing was installed at the centre of the square grid of the PVDs installed in the first pass. After nearly 4 years of consolidation, the top of the slurry had settled more than 3 m. The undrained shear strength had also increased substantially. Therefore the use of PVDs for the improvement of the ultra-soft slurry was successful in this project.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it