Surface Expressions of Rayleigh‐Taylor Instability in Continental Interiors
Bibliographic record
Abstract
Abstract Two‐dimensional thermal‐mechanical numerical models show that Rayleigh‐Taylor‐type (RT) gravitational removal of high‐density lithosphere may produce significant surface deformation (vertical deflection >1000 m) in the interior of a continental plate. A reasonable range of crustal strengths and thicknesses, representing a variation from a stable continental interior to a hot orogen with a thick crust, is examined to study crustal deformation and the surface deflection in response to an RT instability. In general, three types of surface deflection are observed during the RT drip event: (1) subsidence and negative topography; (2) uplift and positive topography; (3) subsidence followed by uplift and inverted topography. One key factor that determines the surface expression is the crustal thickness. Models with a thin crust mainly show subsidence and develop a basin. In the thick crust models, surface expressions are more variable, depending on the crustal strength and depth of high‐density anomaly. With weak crust and a deep high‐density anomaly, the RT drip is decoupled from the overlying crust, and the surface exhibits uplift or little deflection, as the RT drip induces contraction and thickening of the overlying crust. In contrast, with a strong crust and shallow anomaly, the surface is more strongly coupled with the drip and undergoes subsidence, followed by uplift.
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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 | 0.000 |
| 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".