Empirical correlations of compression index for marine clay from regression analysis
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Bibliographic record
Abstract
Single and multiple regression models to estimate the compression index of marine clay in coastal areas in Korea were investigated based on soil property data from more than 1200 consolidation tests on undisturbed samples. Site-specific empirical correlations were proposed to estimate the compression index in terms of both single and multiple soil properties. The proposed regression equations were then compared with the existing empirical equations. It was found that the compression index predicted by a simple linear regression model involving the natural water content, natural void ratio, and liquid limit can reasonably evaluate the real soil compression index. These regression equations may allow a preliminary estimation of the ground settlement for marine clay. It was also recognized that the applications of empirical equations suggested in previous studies result in large uncertainties in estimating the compression index of marine clayey soil in the coastal zone in Korea.Key words: settlement, compression index, regression, statistical analysis, consolidation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it