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Record W4392601658 · doi:10.5194/egusphere-egu24-6348

Martian thermal-contraction polygons as sounders of subsurface properties in Utopia Planitia

2024· preprint· en· W4392601658 on OpenAlexaff
Susan J. Conway, Meven Philippe, R. J. Soare, Lauren E. McKeown

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsDawson College
FundersAgence Nationale de la Recherche
KeywordsPolygon (computer graphics)Wedge (geometry)GeologyMartianMars Exploration ProgramGeometryGeomorphologyAstrobiologyPhysicsMathematicsComputer science

Abstract

fetched live from OpenAlex

On Earth, temperature decreases can cause the thermal contraction of ice-cemented ground. This forms polygonal networks of surficial fractures – called ‘thermal-contraction polygons’ (Washburn, 1956). Polygons exhibit different morphologies with time (Black, 1954): initially showing no relief (‘flat-centred polygons’, FCPs), their margins uplift with the growth of ice or sand wedges (‘low-centred polygons, LCPs); subsequently to wedge degradation, polygon margins then collapse into the wedge casts (‘high-centred polygons, HCPs).On Mars, polygons of similar dimensions (~ 5-25 m in diameter) and morphologies (FCP/LCP/HCP) to those on Earth are commonly observed in the mid-latitudes. They are inferred to form by thermal contraction of ice-cemented ground (Mellon, 1997). Further, polygons in Utopia Planitia (UP) have been identified as ice-wedge polygons (Soare et al., 2021). This indicates a potential role of liquid water in UP during the Amazonian, at a period where the martian climate is thought to be non-conducive to the stability of surface liquid water.Here, we seek to understand whether the characteristics of these ice-wedge polygons could be used to understand the subsurface properties of their substrate. Hence, we investigate the density and type (FCP/LCP/HCP) of polygons for three morphological units in UP, in the area (44-52°N 100-130°E) where polygons were identified as ice-wedge polygons by Soare et al. (2021).In UP, we mapped two morphological units: the “sinuous unit” (elongated, sinuous features) and the “boulder unit” (covered in decametre-scale boulders). We then mapped polygons over the two units using a grid-based technique (Ramsdale et al., 2017).We developed three parameters, that we infer reflect various properties of the ground: ρpol, reflecting the cementation of the substrate by ice; ρwf, reflecting the capacity of the substrate to form wedge ice; ρwp, reflecting capacity of the substrate to preserve ground ice.The boulder unit has no polygons. Therefore, it must be a massive material, non-conducive to ice cementation. Its surface is an extensive field of boulders, and shows blocks shattered in place. It points toward a volcanic origin for the boulder unit. This result is consistent with studies that concluded to the presence of volcanic units in UP (e.g. Tanaka et al., 2005).Our parameters show that the sinuous unit was an initially porous material that became cemented by ice, and underwent wedge formation. Therefore, the sinuous unit was deposited on top of the boulder unit, either as water-rich deposits from a large aqueous flow, which subsequently froze; or by condensation of water vapour from the atmosphere within porous sediment. Those two emplacement modes were suggested to have occurred in UP (e.g. Costard and Kargel, 1995; Séjourné et al., 2012). The sinuous unit was then degraded, exposing the underlying boulder unit.These interpretations show that polygon characteristics can be used to unveil properties of their substrate. In our study zone in UP, it allowed us to link geomorphological units with specific geological processes, that were suggested to have occurred in UP. Therefore, the parameters we developed can be considered as additional tools to study the martian geology at the sub-regional scale.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.025
GPT teacher head0.236
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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