A mantle flow mechanism for the late Paleozoic subsidence of the Paraná Basin
Bibliographic record
Abstract
The Carboniferous‐Permian stage in the evolution of the Paraná Basin is characterized by the long‐wavelength deposition of up to ∼2.5 km of sediment in the continental interior. The tectonics of the region during this time were dominated by convergence and active subduction along the nearby Panthalassan margin of Gondwana. While subsidence in the basin is clearly related to the major tectonic events at the plate margin, there is a distinct delay between the onset of subduction and the initiation of basin deposition. This, and the nature of basin stratigraphy, suggests that the large‐scale subsidence may have been the dynamic response of the lithosphere to mantle flow associated with the penetration of accumulated slab material through the phase change at 660 km depth. We present numerical experiments of mantle convection which show that subducting slabs can stagnate at the 660 km depth phase change and intermittently penetrate through. The associated (negative) dynamic topography remains at relatively low amplitudes as the subducting material pools and then increases rapidly to a maximum during the phase of penetrative flow. We find that the predicted delay time between initial descent of the slab and the maximum surface topography corresponds with evidence from the geological record. Several models of sedimentation based on the evolving dynamic topography are presented, and a simulation generated using infill rates independently estimated for the basin provides a close fit to the amplitude and horizontal length scale of material accumulation in the Paraná Basin.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".