The Surface Texture of Martian Lava Flows as Inferred from Their Decimeter- and Meter-scale Roughness
Bibliographic record
Abstract
Abstract Extensive lava flows are found in the equatorial region of Mars, shaping the surface in a very distinct way. In radar images (at the decimeter scale), these flows are bright, with circular polarization ratios greater than one. This is a typical characteristic of extremely rough, blocky lava flows on Earth. Although the source of the extreme dm-scale roughness of Martian lava flows is unknown, their surface roughness can be constrained at the meter scale in an effort to infer their emplacement style. Here, we utilized high-resolution HiRISE images of Mars to construct digital terrain models of 35 lava flows, and measure their surface roughness parameters at a scale never before examined. Our results show that at the meter scale, Martian lava flows are smoother than blocky flows seen on Earth, and similar in roughness to terrestrial pāhoehoe and rubbly flows, as well as young lunar lava flows. However, these latter flows are much smoother at the decimeter scale than Martian lava flows. The differences observed in the surface roughness of Martian lava flows compared to analog lava flows on Earth and the Moon might be the result of: (1) the differences in the emplacement style of the lava flows, and/or (2) the differences in post-emplacement modification processes on the surface of the lava flows.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".