The Role of Upper Mantle Forces in Post-subduction Tectonics: Insights from 3D Thermo-mechanical Models in the East Anatolian Plateau
Bibliographic record
Abstract
Post-subduction tectonics can involve a wide range of spatiotemporal processes associated with regional and large-scale upper mantle forces. To better understand the interaction between these forces in collisional settings, we focus on active mantle dynamics beneath the East Anatolian Plateau, a well-documented segment of the Arabian-Eurasian continental collision zone. In detail, we use state-of-the-art instantaneous thermomechanical models by combining the advantages of 3D numerical modeling with high-resolution imaging techniques. We analyze the model’s outputs, such as 3D stress-strain and temperature variations of upper mantle convection and reconcile them with numerous geological and geophysical observations. Our results show prominent northward-directed channel flow in the mantle that cuts across the plateau and surroundings, from the Arabian foreland to the Greater Caucasus domain. This result reproduces and elucidates the proposed ~SW-NE-oriented Anatolian Background Splitting pattern and recent seismic low-ultra low-velocity anomalies. We argue that this large-scale upper mantle flow constitutes the engine for the long-wavelength dynamic topography (~400 m) in the region and promotes the relatively small-scale convection pattern by supporting intraplate rift tectonics in the extensional Van Lake zone.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".