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Record W7098724393

Microbial eukaryotic distribution in a dynamic Beaufort Sea and the Arctic Ocean CONNIELOVEJOY * AND MARIANNEPOTVIN

2016· article· en· W7098724393 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticZooplanktonStratification (seeds)PhylotypeBiogeographyPlanktonContinental shelfSea iceTemperature salinity diagrams
DOInot available

Abstract

fetched live from OpenAlex

temperature to salinity stratification of the upper water column. This change coincides with a faunal change as Pacific and Bering Sea zooplankton and fish species are replaced by Arctic species. The clear changes in distributions of larger organisms suggest that the Arctic is an ideal environment to test hypothesis of endemism in single-celled planktonic groups. Here, we investigate the distribution of phylotypes of small protists identified by their 18S rRNA gene. We constructed nine new clone libraries from three different water masses from samples collected along the continental shelf and offshore of Beaufort Sea, Western Canadian Arctic. The new data combined with all other available sequences from the Arctic were used to identify possible phylotypes with restricted Arctic distributions. Among those only reported to date from the Arctic were an oligotrichous ciliate, a chlorarachniophyte and a rhizarian. In the near-surface shelf sample, we also retrieved sequences from Pacific species that had not been previously reported in the Arctic. The occurrences of those phylotypes were best explained by incursions of Pacific Water as coastal currents in combination with elevated temperatures in 2005 that would have been favourable to the non-Arctic phylotypes. Overall, we found support for the notion of microbial biogeography and our results suggest that the Arctic may be vulnerable to microbial community changes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.141

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)0.0000.000

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 head0.007
GPT teacher head0.213
Teacher spread0.205 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicNatural Compound Pharmacology StudiesFrench-language works237,207