Mapping gully-susceptible hillslopes on Mars: implications for their mode of formation and evolution
Bibliographic record
Abstract
Martian gullies display spatial patterns according to latitude, topography, and substrate properties that have been used to provide constraints on formation hypotheses. In this study we generate a map of gully-susceptible terrains across the mid-latitudes of Mars by defining the slope, aspect, and thermal inertia conditions that most gullied hillslopes possess. We mapped all terrains in the midlatitudes that possess these distributive conditions. Our map describes the general distribution of gullies well, and we found 331 previously unidentified gullied hillslopes on gully-susceptible terrains. However, the favorable distributive conditions for gullies cover an area 3 times greater than that of gullied hillslopes, and 79.1 % of these terrains do not display gullies. Correlation between gully-lacking terrains and regions with a high concentration of viscous flow features suggest that gully formation is hindered by topographically forced climates in these regions that either inhibit production of liquid water runoff via melting or the condensation of CO 2 on the surface. We found that gully-lacking regions are not constrained to specifically high or low dust index regions and we suggest that gully and dust distribution are co-incidental effects of atmospheric circulation patterns. Lastly, we observed depressions on gully-lacking hillslopes consistent in morphology with buried gully alcoves, and we propose that these features correspond to ancient gully alcoves that have been buried by glacial deposits, which implies that these potential gullies were formed >5–10 Myr ago.
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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 | 0.001 |
| 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".