Fault Structure and Origin of Compressional Tectonic Features Within the Smooth Plains on Mercury
Bibliographic record
Abstract
Abstract The major physiographic “smooth plains” units on Mercury are dominantly composed of volcanic deposits that have been deformed by horizontal compressive stresses. An open issue is whether these features formed by stresses induced by global contraction, bending stresses due to volcanic loading, or some combination of both. In this study, we model the surface expression of 12 shortening structures within several smooth plains units across Mercury to determine the geometries of the underlying faults. We implement an elastic dislocation model, using both listric and planar fault geometries, to place estimates on the depth of faulting for each feature. We show that a majority of smooth plains shortening structures penetrate the lithosphere to depths greater than 15 km. Thrust faults of this scale have not previously been recognized within the planet's smooth plains units and require a large horizontal stresses to form, which is best explained if this stress arises from global contraction. Further, our results suggest that the observed relief and length contrast between features in the smooth plains units and older intercrater plains units can be explained by interior layering of, and/or a shallower brittle‐ductile transition underlying, the smooth plains units.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".