CPT calibration and analysis for a carbonate sand
Bibliographic record
Abstract
This paper describes a project-based cone penetration test (CPT) calibration on a carbonate sand fill that was hydraulically placed and subsequently densified by vibrocompaction. The project involved the development of an artificial island constructed offshore from the United Arab Emirates for oil and gas production. Carbonate sands have crushable grains and can be significantly more compressible than silica sands, so it was determined that the semi-empirical CPT-based correlations for silica sands were not applicable and a soil-specific calibration was needed for post-densification characterisation of density, shear strength and compressibility. The CPT calibration investigation was primarily undertaken in a centrifuge, and then checked with supplementary tests in a large calibration chamber. In this paper, analysis of the calibration data follows three different threads for comparison with more typical siliceous sands: (a) relationships between CPT tip resistance, void ratio and vertical effective stress; (b) a relationship between CPT tip resistance and state parameter; and (c) an approach based on cavity expansion theory, which provides predictive capability for the CPT once soil properties have been measured in the laboratory. The test results are compared with silica sands, in terms of void ratio or the state parameter ψ.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".