Material-specific interpretation of the state parameter from drained cone penetration test
Bibliographic record
Abstract
The Cone Penetration Test (CPT) is a widely used site investigation tool due to its accuracy and wealth of data at a relatively low cost. Virtually all CPT interpretations explicitly or implicitly depend on how the in-situ state parameter is correlated to the tip resistance. Accurate interpretation of the state parameter from CPT is the basis for evaluating strength and liquefaction susceptibility of granular soils. The handful of interpretation methods used in the industry range between empirical and semi-empirical. As is the case for all empirical methods, extrapolating these methods outside of the original database, especially to significantly different soils such as silt-rich tailings, brings about significant risk. This paper presents a new method of interpreting the state parameter from a fully validated model of the cone penetration in sand. The method has no empirical elements and produces soil-specific correlations between the tip resistance and the state parameter. It can be easily implemented in a spreadsheet and does not require complicated analyses. The method differentiates among soils through calibration of a critical state based constitutive model, Norsand, through triaxial compression tests. The potential errors induced by not measuring soil properties are quantified.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".