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Record W2969916003 · doi:10.1029/2019gl083800

The Methane Diurnal Variation and Microseepage Flux at Gale Crater, Mars as Constrained by the ExoMars Trace Gas Orbiter and Curiosity Observations

2019· article· en· W2969916003 on OpenAlexafffund
John E. Moores, P. L. King, C. L. Smith, Germán Martínez, Claire Newman, Scott D. Guzewich, Pierre‐Yves Meslin, Christopher R. Webster, P. R. Mahaffy, S. K. Atreya, Andrew C. Schuerger

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
FundersScience Mission DirectorateCanadian Space AgencyUniversities Space Research AssociationNational Aeronautics and Space Administration
KeywordsOrbiterMars Exploration ProgramMethaneImpact craterFlux (metallurgy)Atmosphere of MarsEnvironmental scienceAstrobiologyMixing ratioDaytimeTrace gasAtmospheric sciencesVolume (thermodynamics)GeologyMartianPhysicsChemistryAstronomy

Abstract

fetched live from OpenAlex

Abstract The upper bound of 50 parts per trillion by volume for Mars methane above 5 km established by the ExoMars Trace Gas Orbiter, substantially lower than the 410 parts per trillion by volume average measured overnight by the Curiosity Rover, places a strong constraint on the daytime methane flux at the Gale crater. We propose that these measurements may be largely reconciled by the inhibition of mixing near the surface overnight, whereby methane emitted from the subsurface accumulates within meters of the surface before being mixed below detection limits at dawn. A model of this scenario allows the first precise calculation of microseepage fluxes at Gale to be derived, consistent with a constant 1.5 × 10 −10 kg·m −2 ·sol −1 (5.4 × 10 −5 tonnes·km −2 ·year −1 ) source at depth. Under this scenario, only 2.7 × 10 4 km 2 of Mars's surface may be emitting methane, unless a fast destruction mechanism exists.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.274
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations47
Published2019
Admission routes2
Has abstractyes

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