Postcyclic Reconsolidation Strains in Low-Plastic Fraser River Silt due to Dissipation of Excess Pore-Water Pressures
Bibliographic record
Abstract
The postcyclic reconsolidation response of low-plastic Fraser River silt was examined using laboratory direct simple shear testing. Specimens of undisturbed and reconstituted natural low-plastic Fraser River silt and reconstituted quartz powder, initially subjected to constant-volume cyclic loading under different cyclic stress ratios (CSRs) and then reconsolidated to their initial effective stresses (σvo′), were specifically investigated. The volumetric strains during postcyclic reconsolidation (εv-ps) were noted to generally increase with the maximum cyclic excess pore-water pressure (Δumax) and maximum cyclic shear strain experienced by the specimens during cyclic loading. The values of εv-ps and maximum cyclic excess pore-water pressure ratio (ru-max) were observed to form a coherent relationship regardless of overconsolidation effects, particle fabric, and initial (precyclic) void ratio of the soil. The specimens with high ru-max suffered significantly higher postcyclic reconsolidation strains; εv-ps ranging between 1.5 and 5% were noted when ru-max>0.8. The observed εv-ps versus ru-max relationship, when used in combination with the observed dependence of cyclic excess pore-water pressure on CSR and number of load cycles, seems to provide a reasonable approach to estimate postcyclic reconsolidation strains of low-plastic silt.
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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 | 0.000 | 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".