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Record W2975014799 · doi:10.3390/microorganisms7100385

Effects of Vertical Water Mass Segregation on Bacterial Community Structure in the Beaufort Sea

2019· article· en· W2975014799 on OpenAlexafffundabout
Yunyun Fu, Richard B. Rivkin, Andrew S. Lang

Bibliographic record

VenueMicroorganisms · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsArcticPelagic zoneAlphaproteobacteriaSea iceOceanographyEnvironmental scienceMarine ecosystemEcosystemCommunity structureEcologyGeologyBiology

Abstract

fetched live from OpenAlex

The Arctic Ocean is one of the least well-studied marine microbial ecosystems. Its low-temperature and low-salinity conditions are expected to result in distinct bacterial communities, in comparison to lower latitude oceans. However, this is an ocean currently in flux, with climate change exerting pronounced effects on sea-ice coverage and freshwater inputs. How such changes will affect this ecosystem are poorly constrained. In this study, we characterized the bacterial community compositions at different depths in both coastal, freshwater-influenced, and pelagic, sea-ice-covered locations in the Beaufort Sea in the western Canadian Arctic Ocean. The environmental factors controlling the bacterial community composition and diversity were investigated. Alphaproteobacteria dominated the bacterial communities in samples from all depths and stations. The Pelagibacterales and Rhodobacterales groups were the predominant taxonomic representatives within the Alphaproteobacteria. Bacterial communities in coastal and offshore samples differed significantly, and vertical water mass segregation was the controlling factor of community composition among the offshore samples, regardless of the taxonomic level considered. These data provide an important baseline view of the bacterial community in this ocean system that will be of value for future studies investigating possible changes in the Arctic Ocean in response to global change and/or anthropogenic disturbance.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.004
GPT teacher head0.187
Teacher spread0.184 · 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

Citations8
Published2019
Admission routes3
Has abstractyes

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