The Periglacial Landforms and Estimated Subsurface Ice Distribution in the Northern Mid‐Latitude of Mars
Bibliographic record
Abstract
Abstract Subsurface ice in the mid‐latitude regions is a significant water inventory on present‐day Mars, and their volume and distribution are thought to have varied due to the orbitally induced paleoclimatic changes. Using high‐resolution satellite images, the present study explores the distributions of three presumed periglacial landforms (thermal contraction polygons, fractured mounds, and brain terrains) that could provide evidence for the present‐day subsurface ice distribution in the northern mid‐latitude (30°–42°N). We identified the three periglacial landforms concentrated within the regions of 0°–40°E, 60°–100°E, and 160°–210°E in the latitude of >33°N. Their distributions are in agreement with the occurrence of fresh ice‐exposing craters and the estimated area of high annual water ice budget obtained by the general circulation model, reflecting the present‐day subsurface ice distribution. We further classified the thermal contraction polygons into five types based on their morphology, and investigated various distribution patterns for each type. Among them, high‐centered polygons are the most abundant type in the survey area, whereas low‐centered polygons are less prominent and observed only at >38°N. The large‐sized mixture polygons, which were only found in certain areas of 57°–92°E, are distributed in areas where the atmospheric model indicates that the highest annual water ice budget occurred during the past high‐obliquity period, but that the water ice budget has decreased during the present‐day low‐obliquity condition. These findings, along with insights from possible terrestrial analogs in the Arctic Archipelago and northern Canada, suggest that regions where large‐sized mixture polygons formed contained significant amounts of water ice in the past, but have undergone intense degradation over time.
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 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".