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Record W2027340936 · doi:10.1038/srep00604

Vertical distribution of microbial communities in a perennially stratified Arctic lake with saline, anoxic bottom waters

2012· article· en· W2027340936 on OpenAlexafffundabout
A. Comeau, Tommy Harding, Pierre E. Galand, Warwick F. Vincent, Connie Lovejoy

Bibliographic record

VenueScientific Reports · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsDalhousie UniversityUniversité Laval
FundersAboriginal Affairs and Northern Development CanadaNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche ScientifiqueArcticNetFonds Québécois de la Recherche sur la Nature et les TechnologiesParks Canada
KeywordsBiogeochemical cycleAnoxic watersArcticEcologyWater columnOceanographyBenthic zoneCommunity structureEcosystemBiodiversityBiologyChemoclineEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

Meromictic lakes are useful biogeochemical models because of their stratified chemical gradients and separation of redox reactions down the water column. Perennially ice-covered meromictic lakes are particularly stable, with long term constancy in their density profiles. Here we sampled Lake A, a deep meromictic lake at latitude 83°N in High Arctic Canada. Sampling was before (May) and after (August) an unusual ice-out event during the warm 2008 summer. We determined the bacterial and archaeal community composition by high-throughput 16S rRNA gene tag-pyrosequencing. Both prokaryote communities were stratified by depth and the Bacteria differed between dates, indicating locally driven selection processes. We matched taxa to known taxon-specific biogeochemical functions and found a close correspondence between the depth of functional specialists and chemical gradients. These results indicate a rich microbial diversity despite the extreme location, with pronounced vertical structure in taxonomic and potential functional composition, and with community shifts during ice-out.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.222
Teacher spread0.209 · 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 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

Citations116
Published2012
Admission routes3
Has abstractyes

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