Estimating slope of critical state line from cone penetration test — an update
Bibliographic record
Abstract
Estimation of density from cone penetration test (CPT) results is challenging, as cone resistance is a function of a number of soil properties, particularly compressibility. While many of the relevant soil properties can be determined from laboratory testing of recovered samples, this process is not feasible when investigating a deposit of soil with significant variations in gradation and (or) properties across depth and lateral extent. To provide a first-order estimate of density from CPT results alone, a number of correlations have been developed to ascertain other soil properties, particularly compressibility, from CPT data. In particular, friction ratio and soil behaviour type index have been suggested as providing indications of soil compressibility, referenced as the slope of the critical state line. Two of these correlations are critically assessed through the identification and analysis of data from 31 sites where both CPT and relevant laboratory testing were conducted. This process indicates that while the additional data analyzed in this study are generally consistent with previous correlations in terms of trend, significant scatter is evident. In addition, the difficulty in directly relating recovered samples to specific CPT data is outlined.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".