Crustal fabric in the Tibetan Plateau based on waveform inversions for seismic anisotropy parameters
Bibliographic record
Abstract
The Tibetan Plateau has the thickest continental crust on Earth, and fabrics within the crust that are anisotropic to seismic waves may provide clues to how it reached such extreme proportions and how it is currently deforming. Waveform modeling using a global minimization inversion technique applied to receiver functions computed from 11 stations spanning the north‐south length of the eastern plateau has yielded a suite of crustal models that include anisotropy. These models suggest that the Tibetan crust contains 4–14% anisotropy at different depths that is likely a result of both fossil fabrics and more recent deformation. All models contain anisotropy in the surface layer, and for most stations the alignment of the slow symmetry axis suggests a relationship with crustal fabrics associated with E‐W trending thrust faults or sutures. Middle to lower crustal anisotropy is present at most stations with a fast axis trending N‐S to NW‐SE in the south, nearly E‐W in the central plateau, and N‐S to NE‐SW in the northern plateau. This pattern appears consistent with recent ductile deformation due to both topographically induced flow and to boundary forces from subducting lithosphere at the northern and southern margins of the plateau. The orientations of crustal anisotropy determined for most stations in this study are significantly different from shear wave splitting fast polarization directions, implying distinct deformation in the crust and mantle.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".