Evaluation of different methods to identify preconsolidatin pressure of Champlain Sea Clay from CRS tests
Bibliographic record
Abstract
Identifying precisely the preconsolidation pressure of any soil is one of the most challenging geotechnical problems. For sensitive soils, misjudging the preconsolidation pressure can lead to a large overestimation or underestimation of settlement due to the high compressibility after p’c. The performances of eleven graphical identification methods are evaluated on constant rate of strain (CRS) consolidation tests conducted on Champlain Sea clay. The tests include unloading/reloading cycles that are used to evaluate the accuracy of the methods based on known maximum past pressure. A number of numerical procedures are developed to aid in the use of the graphical methods for CRS test data, including locating the inflection point and the point of the maximum curvature on an e-logp curve. Preconsolidation pressure is calculated using straight line equations rather than interpreting it visually. These numerical methods are applied to the test data and their validities and ease of use are evaluated.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".