Soil Characterisation of an Artificial Island Accounting for Heterogeneity
Bibliographic record
Abstract
The heterogeneous nature of soils and other geo-materials results in uncertainty in design and so it is important to incorporate this heterogeneity in analyses of geo-structure performance. However, before analysing the geo-structure itself, it is first necessary to statistically characterise the site in terms of appropriate soil properties. This paper focuses on the description of this first stage in the analysis by presenting a case study. Numerous artificial sand islands were designed and constructed in the Canadian Beaufort Sea, for use as hydrocarbon exploration platforms, in the 1970's and 1980's. For some of these islands, extensive Cone Penetration Test (CPT) data are available for characterising the hydraulically placed sands and for investigating the general factors affecting the in situ density. This paper investigates data from one of these islands. An existing methodology to statistically evaluate CPT data in terms of state parameter is described, the aim being to characterise the deposited sands in terms of state parameter statistics (mean, standard deviation, probability density function and scale of fluctuation). From the results obtained, a discussion on the factors influencing the quality of the fill in terms of in-situ density is presented.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".