Joint analysis of macroscopic response and microfabric evolution of coral sand during earthquake-induced liquefaction
Bibliographic record
Abstract
This study addresses the microfabric evolution of coral sand during earthquake-induced liquefaction using the joint tests of macroscopic shaking table and microscopic X-ray computed tomography. Based on the non-destructive scanning and image reconstruction in three-dimensional, the change in the grain–pore structure of sands under earthquakes is discussed. Furthermore, the special microstructural evolution of coral sand is studied by the contrast tests with Fujian sand. The results show that the coordination number of coral sand is larger than that of Fujian sand after liquefaction, which is consistent with that the reduction in acceleration of coral sand is smaller than that of the Fujian sand, and the coral sand foundation still has a larger shear strength due to the smaller excess pore pressure accumulation. Moreover, the contact index of Fujian sand and Reigate sand fluctuates in a similar range with the change of void ratio and coordination number compared with coral sand. This is due to the fact that the Fujian sand and Reigate sand are both general terrigenous sands (quartz sand), while coral sand has irregular particle shapes and larger surface friction caused by marine biogenesis. The test results deepen the understanding of the liquefaction mechanism of coral sand.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".