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Record W2076959750 · doi:10.1099/mic.0.047837-0

Major players on the microbial stage: why archaea are important

2011· review· en· W2076959750 on OpenAlexaff
Ken F. Jarrell, Alison D. Walters, C. Bochiwal, Juliet M. Borgia, Thomas E. Dickinson, J. Chong

Bibliographic record

VenueMicrobiology · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsQueen's University
FundersBiotechnology and Biological Sciences Research Council
KeywordsArchaeaBiologyThree-domain systemEcologyEvolutionary biologyBacteriaGenetics

Abstract

fetched live from OpenAlex

As microbiology undergoes a renaissance, fuelled in part by developments in new sequencing technologies, the massive diversity and abundance of microbes becomes yet more obvious. The Archaea have traditionally been perceived as a minor group of organisms forced to evolve into environmental niches not occupied by their more 'successful' and 'vigorous' counterparts, the bacteria. Here we outline some of the evidence gathered by an increasingly large and productive group of scientists that demonstrates not only that the Archaea contribute significantly to global nutrient cycling, but also that they compete successfully in 'mainstream' environments. Recent data suggest that the Archaea provide the major routes for ammonia oxidation in the environment. Archaea also have huge economic potential that to date has only been fully realized in the production of thermostable polymerases. Archaea have furnished us with key paradigms for understanding fundamentally conserved processes across all domains of life. In addition, they have provided numerous exemplars of novel biological mechanisms that provide us with a much broader view of the forms that life can take and the way in which micro-organisms can interact with other species. That this information has been garnered in a relatively short period of time, and appears to represent only a small proportion of what the Archaea have to offer, should provide further incentives to microbiologists to investigate the underlying biology of this fascinating domain.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.036
GPT teacher head0.263
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations72
Published2011
Admission routes1
Has abstractyes

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