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Record W2131426773 · doi:10.1017/s0954102000000420

Evolutionary origins of Antarctic microbiota: invasion, selection and endemism

2000· article· en· W2131426773 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAntarctic Science · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEndemismBiodiversityEcologyBiologyHabitatEcological nicheEcosystem

Abstract

fetched live from OpenAlex

Increasing interest in the ecological roles, conservation and biotechnological potential of Antarctic microbiota has focused attention on their biodiversity and evolutionary origins. Antarctic microbial ecosystems provide useful models for general questions in evolutionary ecology given the relative isolation of the South Polar Region, the severe biological constraints imposed by the polar environment, and the absence of higher plants and animals in some Antarctic habitats. Sealed environments such as Lake Vostok and the overlying East Antarctic ice sheet provide unique, natural culture collections for studying microorganisms that have been isolated from the global gene pool over timescales of evolutionary significance. Most Antarctic environments, however, continue to receive microbial propagules from outside the region, as indicated by spore trap data, the microflora found in Antarctic snow and ice, the colonising taxa at geothermal sites, and the high frequency of apparently cosmopolitan species in most habitats. Differences in environmental stability and selection pressure among environments are likely to influence the degree of adaptive radiation and microbial endemism. The latter seems greater in the Southern Ocean by comparison with non-marine ecosystems of Antarctica, although there is some evidence of endemic species in highly specialised niches on the continent such as in the endolithic habitat and saline lakes. Analytical techniques such as 16S rDNA sequencing and DNA–DNA hybridisation are beginning to provide new insights into the genetic affinities and biodiversity of Antarctic microbiota, and are leading to a more rigorous evaluation of microbial endemism.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.010
GPT teacher head0.243
Teacher spread0.234 · 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