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Stress response of methanogenic archaea from Siberian permafrost compared with methanogens from nonpermafrost habitats

2007· article· en· W1853288868 on OpenAlexfundno aff
Daria Morozova, Dirk Wagner

Bibliographic record

VenueFEMS Microbiology Ecology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftMcGill University
KeywordsArchaeaPermafrostBiologyExtremophileSalinityDesiccationExtreme environmentEcologyMethanogenesisMethanogenPsychrophileBotanyMicroorganismMethaneBacteriaEnzymeBiochemistry

Abstract

fetched live from OpenAlex

We examined the survival potential of methanogenic archaea exposed to different environmental stress conditions such as low temperature (down to -78.5 degrees C), high salinity (up to 6 M NaCl), starvation (up to 3 months), long-term freezing (up to 2 years), desiccation (up to 25 days) and oxygen exposure (up to 72 h). The experiments were conducted with methanogenic archaea from Siberian permafrost and were complemented by experiments on well-studied methanogens from nonpermafrost habitats. Our results indicate a high survival potential of a methanogenic archaeon from Siberian permafrost when exposed to the extreme conditions tested. In contrast, these stress conditions were lethal for methanogenic archaea isolated from nonpermafrost habitats. A better adaptation to stress was observed at a low temperature (4 degrees C) compared with a higher one (28 degrees C). Given the unique metabolism of methanogenic archaea in general and the long-term survival and high tolerance to extreme conditions of the methanogens investigated in this study, methanogenic archaea from permafrost should be considered as primary candidates for possible subsurface Martian 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.382
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.010
GPT teacher head0.224
Teacher spread0.214 · 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.

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

Citations82
Published2007
Admission routes1
Has abstractyes

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