The Surface Roughness of Large Craters on Mercury
Bibliographic record
Abstract
Abstract This study investigates how individual large craters on Mercury (diameters of 25–200 km) can produce surface roughness over a range of baselines (the spatial horizontal scale) from 0.5 to 250 km. Surface roughness is a statistical measure of change in surface height over a baseline usually after topography has been detrended. We use root mean square deviation as our measure of surface roughness. Observations of large craters on Mercury at baselines of 0.5–10 km found higher surface roughness values at the central uplifts, rims, and exteriors of craters, while the crater floors exhibit the lowest roughness values. At baselines <10 km, the regions exterior to large craters with diameters >80 km have the highest surface roughness values. These regions, which include the ejecta and secondary fields, are the main contributors to the increased surface roughness observed in high‐crater density regions. For baselines larger than 10 km, the crater cavity itself is the main contributor to surface roughness. We used a suite of numerical models, utilizing the measured surface roughness obtained in the study, to model the cumulative effect of adding large craters to a surface. The results indicate that not all of the surface roughness on Mercury is due to fresh large craters but that impact craters likely contribute to the Hurst exponent from baselines of 0.5–1.5 km and the shape of the deviogram. The simulations show that the surface roughness varied around an asymptote at the baselines studied before the surface was covered in impact craters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".