Correlations between <i>P</i>-wave velocity and Atterberg limits of cohesive soils
Bibliographic record
Abstract
Undisturbed and disturbed samples of cohesive soils were collected from eight different locations to investigate the possibility of estimating the Atterberg limits of cohesive soils from P-wave velocity measurements. Each soil type was classified according to the Unified Soil Classification System, and then Atterberg limits of soils were determined and P-wave velocity measurements carried out on the undisturbed samples of each soil type. P-wave velocity values were correlated with the corresponding values of Atterberg limits. It was found that liquid limit, plastic limit, and plasticity index exhibit good correlations with P-wave velocity. The relations follow a logarithmic function. Liquid limit, plastic limit, and plasticity index decrease with an increase in P-wave velocity. In addition, liquid limit, plastic limit, and plasticity index exhibit very good correlations with the ratio of P-wave velocity to water content. Liquid limit, plastic limit, and plasticity index decrease logarithmically with an increase in the ratio of P-wave velocity to water content. It can be concluded that the Atterberg limits of cohesive soils can be predicted from P-wave velocity measurements for preliminary investigations. The developed equations have some limitations and further study is required in this area.Key words: Atterberg limits, cohesive soils, P-wave velocity, regression analysis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".