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Record W7020861263

Microbial Ecology of Dry Permafrost from Elephant Head, Antarctica

2023· dissertation· en· W7020861263 on OpenAlexfundno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNuclear Safety and Security CommissionPolar Knowledge CanadaNational Aeronautics and Space Administration
KeywordsPermafrostMicrocosmMicrobial ecologyMicroorganismExtremophileMicrobial population biologyArthrobacterAdaptation (eye)
DOInot available

Abstract

fetched live from OpenAlex

The objective of this thesis is to determine if a viable, active microbial community could persist in cold, oligotrophic, dry permafrost soils from Elephant Head, Antarctica. Low amounts of microbial activity were measured in some microcosm samples at 5, 0, and -5C, as assessed using radiorespiration assays with radiolabeled acetate as a carbon source. Microbial communities were similar to other Antarctic environments and appear adapted for survival to cold, dry, oligotrophic conditions based on metagenomic, bacterial and fungal amplicon sequencing. The presence of viable microorganisms was confirmed through cultivation which isolated ~20 psychrotrophic organisms including Arthrobacter agilis strain Ant-EH-1 which is capable of cell division at -5C. The genome of A. agilis Ant-EH-1 was sequenced and was found to contain many genes for adaptation to cold, oligotrophic conditions. Together these results show that dry permafrost environments do not exclude active microbial life at sub-zero temperatures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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