Rapid surface uplift and crustal flow in the Central Andes (southern Peru) controlled by lithospheric drip dynamics
Bibliographic record
Abstract
The high flux magmatism, crustal shortening/extension and plateau formation in Cordilleran orogenic systems have been explained by removal of lithosphere (lower crust and the sub-arc mantle lithosphere) that develops beneath the magmatic arc and hinterland regions. However, the primary role of this process driving surface uplift, and crustal deformation is not well understood. Here, reconciling geodynamic model predictions with lithospheric structure and paleoelevation estimates, we suggest that viscous drip-type lithospheric removal from beneath the Central (Peruvian) Andes can explain several tectonic features: (1) "double humped" shaped/axisymmetric topographic profile and rapid surface rise (up to 1.2 km in ~ 4.31 Myrs); (2) thicker crust associated with the lower surface elevation of the Altiplano plateau (Lake Titicaca region) (negative residual topography) and higher topography and thinner crust of Western and Eastern Cordilleras (positive residual topography); and (3) faster wave speed (colder)/sub-Moho anomaly underlying the Altiplano, surrounded by slower speed anomalies on both western arc-forearc areas and parts of the eastern Cordillera and Sub-Andes. Our results emphasize the important role of lithospheric drip and associated mantle dynamics in the transient evolution of Andean orogeny controlling surface uplift and crustal flow and thickening.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".