Embankment on sludge: predicted and observed performances
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
The case history of an embankment built over soft water-treatment sludge is presented. To assure that the sludge would consolidate and gain strength as predicted, a test embankment was built. The observed performance of the test embankment was compared with the predicted performance to verify and modify design assumptions. The results were used to design and construct the full-scale embankment. The finite element method and the critical state model were used to predict the performances of the test embankment and the full-scale embankment. Bayesian updating and system identification were used to update the material properties used in the prediction for the test embankment. The updated properties were then used to update the prediction for the test embankment and to predict the performance of the full-scale embankment. These predictions were compared with the observed performances to evaluate the accuracies of the predictions with different input data. Efforts were made to identify factors that cause differences between predicted and measured performances.Key words: Bayesian updating, consolidation, finite-element prediction, shear strength, stability, water-treatment sludge.
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 | 0.000 |
| 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 | 0.001 |
| 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