Characterization of silty soil thin layering and groundwater conditions for liquefaction assessment
Bibliographic record
Abstract
Tools for characterizing thin layering and groundwater table conditions are evaluated at silty soil sites being assessed for liquefaction. Thin interlayered stratigraphy and groundwater table fluctuation are two potential causes for inconsistencies observed during the Canterbury earthquake sequence, wherein liquefaction did not manifest at several silty soil sites, despite simplified liquefaction assessment procedures indicating severe manifestations would be expected. Site investigations should capture these features to allow for improved assessment of liquefaction potential at silty soil sites. Cone penetration tests (CPTs), mini-CPTs, and sonic borings do not adequately capture thin layering. However, detailed logging of high-quality samples captures the actual in situ layering that may help explain the limitations of simplified liquefaction assessment procedures at these sites, revealing the need to understand underlying limitations in current site investigation techniques. Piezometers, sonic borings, high-quality sampling, crosshole testing, and regional groundwater maps are evaluated to assess their ability to capture complex groundwater conditions. Multiple groundwater measurement methods are typically required to characterize groundwater fluctuations. An approach to using enhanced site characterization tools is recommended for liquefaction assessments at silty soil sites with thin layering and groundwater fluctuations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".