Correction of Mechanical CPT Data for Liquefaction Resistance Evaluation
Bibliographic record
Abstract
For more than 30 years, there has been considerable interest in using CPT also to evaluate the liquefaction resistance of soils.Unfortunately, most of the simplified methods used for liquefaction resistance evaluation only require in situ measurements from electrical cone penetrometers even if they are frequently applied using measurements from mechanical CPTs that are still preferred by current engineering practice in many countries.Erroneous estimates of liquefaction resistance and relevant non-conservative results are obtained by applying electrical CPT-based methods to mechanical CPT data without any form of correction.This study focuses on the developing of an appropriate procedure for correcting mechanical CPT data and provides modified equations for liquefaction resistance estimation by means of electrical CPT-based simplified methods.A dataset of more than 3900 pairs of measurements of cone tip resistance and sleeve friction were obtained from 44 sites selected in Northern and Central Italy and processed by means of statistical analyses.Suitable adjustments to CPT mechanical data were proposed for determining corrected liquefaction potential.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".