Diffuse Deformation in the SE Tibetan Plateau: New Insights From Geodetic Observations
Bibliographic record
Abstract
Abstract The southeastern Tibetan Plateau is a key component in the India‐Eurasia collision zone, which is characterized by spatially prevalent strike‐slip fault systems with devastating earthquakes. However, slip rates on some of these faults are still poorly constrained, hindering an understanding of kinematic and dynamic processes in this region. We analyze contemporary crustal deformation in the SE Tibetan Plateau based on the latest, dense geodetic observations. Slip rates on a set of dextral NW/NNW‐striking faults are determined using a 3‐D elastic half‐space dislocation model. Our results show that boundary faults such as the Red River and Lancangjiang faults yield dextral slip rates ranging from 1 to 3 mm/a, similar to those of other small‐scale sub‐parallel faults such as the Chuxiong, Qujiang, and Wuliangshan faults. Additionally, sinistral slip of the Xiaojiang fault may have partly transferred to transpressional slip on the Qujiang, Jianshui, and central Red River faults, which increase seismicity on these faults. New seismic relocation results, geodetic measurements, and existing structural observations show the geometry of this dextral fault system at the depth, which may be restricted above or within the rheologically weak mid‐lower crust rather than cutting into the mantle. Results confirm that the SE Tibetan Plateau is characterized by on‐going diffuse deformation between the Sagaing and Xianshuihe‐Xiaojiang faults. Driven by the northward advance of the eastern Himalayan syntaxis and southward crustal extrusion, distributed right‐lateral movements occurred along the NW/NNW‐striking fault system.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".