New Insights Into Crustal and Mantle Flow Beneath the Red River Fault Zone and Adjacent Areas on the Southern Margin of the Tibetan Plateau Revealed by a 3‐D Magnetotelluric Study
Bibliographic record
Abstract
Abstract A number of geodynamic models have been proposed for the southeastern margin of the Tibetan plateau and include a range of deformation processes. One unresolved issue is whether crustal and mantle flow occurs, and if it does, how flow contributes to the mass balance of the India‐Asia collision. To address this question, new magnetotelluric data were collected and used to derive a three‐dimensional electrical resistivity model of the crust and upper mantle beneath the Red River Fault (RRF) zone and adjacent areas. The most prominent features of the model are (1) a resistor in the upper‐middle crust directly beneath the trace of the RRF; (2) a major change in upper mantle resistivity across the RRF; and (3) a significant conductor in the upper mantle northeast of the RRF, which extends upward into the crust, and which requires a melt fraction of up to 3%. The model suggests that the lower crustal conductors may be due to melt/fluids derived from the mantle, rather than from outward flow from Tibet. The most likely source of fluids and melts could be upwelling mantle flow related to the Hainan mantle plume. The change in resistivity across the RRF implies a change in lithospheric strength may explain the present‐day localization of deformation and uplift at this location. The resistivity model may also give insights into the distribution of ore deposits in Ailao Shan, since many mineral deposits are derived from magmatic fluids generated in the mantle at the edges of regions of thick lithosphere.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".