Interpretation of the limits in shear strength in binary granular mixtures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many natural slopes and rockfill structures are made of a mixture of rock fragments and sand-size particles. To analyze the stability of such natural slopes and rockfills, a knowledge of how rocksand mixtures develop their shear strength is needed. Laboratory tests conducted on mixtures of glass beads of two different sizes (5 and 0.4 mm) have indicated that their shear strength depends upon the relative concentration by weight of the large and small beads in the mixtures. If the concentration by weight of the large beads is greater than 70%, the shear strength of the mixtures is controlled by the frictional resistance of the large beads. If the concentration of the large beads is less than 40%, the shear strength of the mixtures is controlled by the frictional resistance of the small beads. If the concentration of the large beads is between 40 and 70%, the shear strength of the mixture is partially controlled by the frictional resistance provided by the large beads in the mixtures. These limits are very similar to those reported for rocksand mixtures. To date, no explanation has been put forward to account for why these limits exist. This study presents an explanation for their existence. The explanation is based on the porosity developed by the mixtures and the type of structural support provided by the coarse and fine grains.Key words: shear strength, granular mixtures, porosity, fabric, compaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it