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Record W3039012254 · doi:10.1038/s41598-020-67815-8

The identification of sulfide oxidation as a potential metabolism driving primary production on late Noachian Mars

2020· article· en· W3039012254 on OpenAlexfundaboutno aff
Michael C. Macey, Mark Fox‐Powell, Nisha K. Ramkissoon, Ben Stephens, T. Barton, S. P. Schwenzer, V. K. Pearson, C. R. Cousins, Karen Olsson‐Francis

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilNatural Resources CanadaLeverhulme Trust
KeywordsNoachianMars Exploration ProgramSulfidePrimary (astronomy)Identification (biology)Production (economics)AstrobiologyChemistryBiologyEcologyMartianPhysicsEconomics

Abstract

fetched live from OpenAlex

The transition of the martian climate from the wet Noachian era to the dry Hesperian (4.1-3.0 Gya) likely resulted in saline surface waters that were rich in sulfur species. Terrestrial analogue environments that possess a similar chemistry to these proposed waters can be used to develop an understanding of the diversity of microorganisms that could have persisted on Mars under such conditions. Here, we report on the chemistry and microbial community of the highly reducing sediment of Colour Peak springs, a sulfidic and saline spring system located within the Canadian High Arctic. DNA and cDNA 16S rRNA gene profiling demonstrated that the microbial community was dominated by sulfur oxidising bacteria, suggesting that primary production in the sediment was driven by chemolithoautotrophic sulfur oxidation. It is possible that the sulfur oxidising bacteria also supported the persistence of the additional taxa. Gibbs energy values calculated for the brines, based on the chemistry of Gale crater, suggested that the oxidation of reduced sulfur species was an energetically viable metabolism for life on early Mars.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.378

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 communication0.0000.001
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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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

Citations37
Published2020
Admission routes2
Has abstractyes

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