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Record W158319340

Martian Glacial Morphology, Geomorphology, and Atmospheric Methane

2007· article· en· W158319340 on OpenAlexaboutno aff
D. S. McMenamin, G. E. McGill

Bibliographic record

VenueLPI · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsMartianMethaneGeologyGlacierMeltwaterMars Exploration ProgramGlacial periodAstrobiologyCryosphereAtmospheric methaneNoachianAtmosphere of MarsClathrate hydrateAtmospheric sciencesGeomorphologyClimatologyHydrateOceanographySea iceChemistryPhysicsGreenhouse gas
DOInot available

Abstract

fetched live from OpenAlex

Introduction: We have earlier proposed [1] that methane clathrate hydrate in martian glacial ice could be responsible for both current martian atmospheric methane and for signs of past martian glacial melt. We further explore this idea, and compare it to the similar hypothesis of Prieto-Ballesteros, et al. [2]. Background: The presence of methane in the martian atmosphere [3-5] is intriguing, because methane’s photochemical stability on Mars is short [3], and nearly all terrestrial methane is biogenic. The mixing ratio is highest in water-rich areas, but varies greatly, suggesting that it is released from highly localized sources [4]. The existence of geomorphology resembling terrestrial glacial meltwater features is also puzzling, as martian surface temperatures, atmospheric pressure, gravity, and geothermal heat flux suggest that martian glaciers since the Noachian should be coldbased [6-7], even during periods of warm climate [1]. Methane release loci: Data from the Planetary Fourier Spectrometer (PFS) show highly variable mixing ratios, implying localized sources [4]. Allen et al. [8] seek correlations between methane and geologic structures. Work by McMenamin and McGill [1] and Prieto-Ballesteros, et al. [2] suggests that the correlation will be with remnant glacial features, such as those demonstrated by Head, et al. [9]. PrietoBallesteros et al. [2] propose that methane is released from cryospheric hydrates destabilized by the retreat of sublimating glaciers. As seen in Figure 1, this is minor compared to the amount destabilized within the remnant glacier itself. A glacial or cryospheric reservoir of methane does not constrain the ultimate source of the methane, which could be produced by microbe or abiotic geological processes. Meltwater sources: The most likely sources of subglacial meltwater are local geothermal activity (limited to certain times and places), increased basal temperature due to the insulating properties of dust or gas hydrates, or lowered melting point due to inclusion of salts, gases, or gas hydrates [1]. Catastrophic dissociation of cryospheric gas hydrates may have caused chaos terrain and outflow channels [10,11]. Why methane hydrate: The fact that methane hydrate can explain both geomorphological features and atmospheric chemistry makes it an elegant solution to both problems. Carbon dioxide hydrate, which may also exist on Mars, would form where the CO2-rich atmosphere interacts with ice, i.e., at the surface, and probably only near the poles [11,12]; concentrations of CO2 hydrate are unlikely [10]. Methane hydrate formation, whether due to microbes or geologic processes, can occur within the hydrate stability zone (HSZ). In the HSZ, hydrates form spontaneously if the appropriate molecules are present, though the presence of salts inhibits them. Max and Clifford [10, 13] showed that a HSZ should begin at ~15 m below the surface of bare, ice-saturated regolith. Extrapolating from their results and assuming a glacial ice density of ~910 kg m [14], methane hydrate should be stable beneath a mere ~38.5 m of glacial ice [1]. Methane hydrate dissociates below the melting point of water ice, and increases greatly in volume

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 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 score0.009
Threshold uncertainty score0.019

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.007
GPT teacher head0.225
Teacher spread0.217 · 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".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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