Experimental constraints on the relationship between clay abundance, clay fabric, and frictional behavior for the <scp>C</scp>entral <scp>D</scp>eforming <scp>Z</scp>one of the <scp>S</scp>an <scp>A</scp>ndreas <scp>F</scp>ault
Bibliographic record
Abstract
Abstract The presence of smectite (saponite) in fault gouge from the Central Deforming Zone of the San Andreas Fault at Parkfield, CA has been linked to low mechanical strength and aseismic slip. However, the precise relationship between clay mineral structure, fabric development, fault strength, and the stability of frictional sliding is not well understood. We address these questions through the integration of laboratory friction tests and FIB‐SEM analysis of fault rock recovered from the San Andreas Fault Observatory at Depth (SAFOD) borehole. Intact fault rock was compared with experimentally sheared fault gouge and different proportions of either quartz clasts or SAFOD clasts extracted from the sample. Nano‐textural measurements show the development of localized clay particle alignment along shear folia developed within synthetic gouges; such slip planes have multiples of random distribution (MRD) values of 3.0–4.9. The MRD values measured are higher than previous estimates (MRD 1.5) that show lower degrees of shear localization and clay alignment averaged over larger volumes. The intact fault rock exhibits less well‐developed nano‐clay fabrics than the experimentally sheared materials, and MRD values decrease with smectite content. We show that the abundance, strength, and shape of clasts all influence fabric evolution via strain localization: quartz clasts yield more strongly developed clay fabrics than serpentine‐dominated SAFOD clasts. Our results suggest that (1) both clay abundance and the development of nano‐scale fabrics play a role in fault zone weakening and (2) aseismic creep is promoted by slip along clay shears with >20 wt % smectite content and MRD values ≥2.7.
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.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".