Equivalent number of uniform cycles versus earthquake magnitude relationships for fine-grained soils
Bibliographic record
Abstract
In current geotechnical seismic design practice, the empirical correlation between equivalent number of uniform cycles (N eq ) of shaking and earthquake magnitude (M w ) forms an integral part of liquefaction potential evaluation. This relationship, in turn, is used to derive the magnitude scaling factors that are commonly used in field-based liquefaction evaluation procedures. The N eq versus M w relationship for liquefaction assessment was examined for fine-grained soils using time-histories in the range 5 < M w ≤ 9, especially including strong ground motion time-histories from the latest subduction zone earthquakes with M w > 8.0. The experimental database available from cyclic direct simple shear tests conducted on natural fine-grained soils retrieved from undisturbed soil sampling was used to obtain the cyclic shear resistance weighting curves for the study. The work presented herein has contributed to further improving the current models used to represent magnitude scaling factor (MSF) values for large earthquake magnitudes and the functional dependency of this parameter on soil type. The MSF–M w curve derived for low-plastic Fraser River Delta silt lies in-between the MSF curves derived for clean sand and clay, resonating with the inferences that have been made that the silt behavior can neither be considered sand-like nor clay-like.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".