The Role of Crustal Fluids in Strike-slip Tectonics: New Insights from Magnetotelluric Studies
Bibliographic record
Abstract
Abstract: The presence of fluids in the EarthÕs crust can dramatically change the rheology and may control a wide range of tectonic processes, especially in regions characterized by strike-slip deformation. Fluids such as water and partial melt change the electrical resistivity of the subsurface and may be detected through geophysical techniques that remotely sense electrical resistivity. For imaging to crustal and upper mantle depths, the most useful technique is magnetotellurics (MT) that uses natural electromagnetic waves as an energy source. Magnetotelluric studies of the Tibetan Plateau have detected a widespread mid-crustal layer of partial melting across almost the entire north-south extent of the plateau. This provides a locus for deformation that decouples the upper and lower parts of the lithosphere and allows the continued convergence of India and Asia to extrude the Asian lithosphere to the east. The melt layer terminates at the North Kunlun fault, one of the major strike-slip faults that accommodate the eastward extrusion. A detailed magnetotelluric study of the San Andreas Fault in Central California has imaged a wedge of fractured, fluid-saturated rock in the upper 3—5 km of the fault zone. The micro-earthquake distribution shows that seismicity begins at the base of this zone. Fault segments with a higher fluid budget exhibit creep, while the relatively dry fault segments are generally locked.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".