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Record W2921639275 · doi:10.3389/fmicb.2019.00426

An Ionic Limit to Life in the Deep Subsurface

2019· article· en· W2921639275 on OpenAlexfundno aff
Samuel J. Payler, Jennifer F. Biddle, Barbara Sherwood Lollar, Mark Fox‐Powell, Thomas W. D. Edwards, Bryne T. Ngwenya, S.M. Paling, Charles S. Cockell

Bibliographic record

VenueFrontiers in Microbiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsLimit (mathematics)Ionic bondingBiochemical engineeringEnvironmental scienceChemistryBiologyNanotechnologyBiological systemMaterials scienceMathematicsIonEngineeringMathematical analysis

Abstract

fetched live from OpenAlex

The physical and chemical factors that can limit or prevent microbial growth in the deep subsurface are not well defined. Brines from an evaporite sequence were sampled in the Boulby Mine, United Kingdom between 800 and 1300 m depth. Ionic, hydrogen and oxygen isotopic composition were used to identify two brine sources, an aquifer situated in strata overlying the mine, and another ambiguous source distinct from the regional groundwater. The ability of the brines to support microbial replication was tested with culturing experiments using a diversity of inocula. The examined brines were found to be permissive for growth, except one. Testing this brine's physicochemical properties showed it to have low water activity and to be chaotropic, which we attribute to the high concentration of magnesium and chloride ions. Metagenomic sequencing of the brines that supported growth showed their microbial communities to be similar to each other and comparable to those found in other hypersaline environments. These data show that solutions high in dissolved ions can shape the microbial diversity of the continental deep subsurface biosphere. Furthermore, under certain circumstances, complex brines can establish a hard limit to microbial replication in the deep biosphere, highlighting the potential for subsurface uninhabitable aqueous environments at depths far shallower than a geothermally-defined limit to life.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.001

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 head0.005
GPT teacher head0.203
Teacher spread0.198 · 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; both teacher heads agree on what is shown here.

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

Citations54
Published2019
Admission routes1
Has abstractyes

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