Landforms indicative of regional warm based glaciation, Phlegra Montes, Mars
Bibliographic record
Abstract
Viscous flow features (VFF) occur in the mid-latitudes of Mars and have characteristics consistent with being glaciers. Climate models suggest that martian glaciers are cold-based systems in which meltwater has never been widely produced. VFF are common in Phlegra Montes, a mountain range in the mid-latitudes of the northern hemisphere of Mars. However, in Phlegra Montes, the presence of an esker associated with an extant Amazonian Period VFF provides evidence that warm-based glacial processes did formerly operate. The problem at the centre of this paper is that the glacial meltwater responsible for this esker could have been produced as a consequence of its setting in a graben, with locally enhanced geothermal heating having been the driver of melt, not systemic heating associated with a regional warm-based regime. Given this uncertainty, this paper aims to determine if there are indicators of more widespread warm-based glacial processes in Phlegra Montes. The paper briefly describes the distribution and characteristics of VFF across the region, before focussing on the search for key landforms considered diagnostic of erosion by warm-based glaciers. From our observations, including discriminant morphometrics, we conclude that the landscape of Phlegra Montes is indicative of widespread warm-based glacial processes, including subglacial scour, linear abrasion and the incision of subglacial meltwater channels. Our findings have significance in constraining the contexts and process environments within which liquid water has been produced during the Amazonian Period on Mars and point to several lines of future research into martian glaciation, climate and landscape evolution .
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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 | 0.000 |
| 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) | 0.002 | 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".