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Record W2954844625 · doi:10.1029/2019je006005

High Survivability of Micrometeorites on Mars: Sites With Enhanced Availability of Limiting Nutrients

2019· article· en· W2954844625 on OpenAlexaff
Andrew G. Tomkins, M. J. Genge, Alastair W. Tait, S. L. Alkemade, Andrew Langendam, Prudence P. Perry, Sasha Wilson

Bibliographic record

VenueJournal of Geophysical Research Planets · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Alberta
FundersAustralian Research CouncilScience and Technology Facilities Council
KeywordsMars Exploration ProgramMartianAstrobiologyNutrientMartian surfaceAeolian processesLimitingMeteoriteEnvironmental scienceEarth scienceGeologyChemistryGeomorphologyBiology

Abstract

fetched live from OpenAlex

Abstract NASA's strategy in exploring Mars has been to follow the water, because water is essential for life, and it has been found that there are many locations where there was once liquid water on the surface. Now perhaps, to narrow down the search for life on a barren basalt‐dominated surface, there needs to be a refocusing to a strategy of “follow the nutrients.” Here we model the entry of metallic micrometeoroids through the Martian atmosphere, and investigate variations in micrometeorite abundance at an analogue site on the Nullarbor Plain in Australia, to determine where the common limiting nutrients available in these (e.g., P, S, Fe) become concentrated on the surface of Mars. We find that dense micrometeorites are abundant in a range of desert environments, becoming concentrated by aeolian processes into specific sites that would be easily investigated by a robotic rover. Our modeling suggests that micrometeorites are currently far more abundant on the surface of Mars than on Earth, and given the far greater abundance of water and warmer conditions on Earth and thus much more active weather system, this was likely true throughout the history of Mars. Because micrometeorites contain a variety of redox sensitive minerals including FeNi alloys, sulfide and phosphide minerals, and organic compounds, the sites where these become concentrated are far more nutrient rich, and thus more compatible with chemolithotrophic life than most of the Martian surface.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.313

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 studies0.0000.000
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 head0.032
GPT teacher head0.295
Teacher spread0.263 · 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 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

Citations19
Published2019
Admission routes1
Has abstractyes

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