Uniform cyclic direct simple shear tests on Ottawa F65 sand, in Direct simple shear testing on Ottawa F65 sand under uniform and irregular cyclic loading
Bibliographic record
Abstract
Uniform cyclic Direct Simple Shear (DSS) experiments were conducted on reconstituted specimens of Ottawa F-65 sand. Ottawa F-65 sand is classified as a poorly graded sand (SP, classified in accordance with ASTM 2017), with a median grain size (D50) of 0.20 mm, a coefficient of uniformity (Cu) of 1.47, a coefficient of curvature (Cc) of 0.88, and no fines (Carey et al. 2020). In this study, values of emin and emax of 0.51 and 0.78, respectively, were selected as more reliable based on the statistical analysis of the properties of Ottawa F-65 sand by Carey et al. (2020). An electromechanical dynamic cyclic simple shear (EMDCSS) device manufactured by GDS Instruments was utilized to perform constant-volume (equivalent undrained) cyclic DSS tests. The active height control system implemented in the EMDCSS device allowed constant-volume DSS tests to be performed with vertical strains below threshols suggested in the literature. Data raw files include four space separated columns of shear strain (%), shear stress (kPa), vertical stress (kPa), and axial strain (%). Users can plot stress strain loops, stress paths, loss of vertical stress vs strain, the evolution of equivalent pore pressure pressure (not measured directly but extrapolated as loss of effective stress), and check for vertical compliance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".