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Record W4404310033 · doi:10.1139/as-2024-0044

Seasonality and interannual variability of an Arctic marine time series, IsA

2024· article· en· W4404310033 on OpenAlexvenueno aff
Anna Vader, Eleanor R Handler, Ragnheid Skogseth, Aud Larsen, Tove M. Gabrielsen

Bibliographic record

VenueArctic Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSeasonalitySeries (stratigraphy)ArcticClimatologyEnvironmental scienceThe arcticOceanographyGeographyGeologyMathematicsStatistics

Abstract

fetched live from OpenAlex

The Arctic is warming twice as fast as anywhere else on the planet, in the European Arctic mainly driven by exalted Atlantic Water inflow. Microbial eukaryotes are diverse and essential to the functioning of marine ecosystems, thus environmental perturbations altering their communities influence the entire ecosystem. To study seasonal and interannual variation and the potential effects of Atlantification, a long-term marine time series has been established in Isfjorden-Adventfjorden, West Spitsbergen. We here present 3 years of high-resolution data including hydrography, nutrients, photosynthetic biomass, flow cytometry and community composition of microbial eukaryotes (0.45–10 µm, based on Illumina metabarcoding of 18S rDNA and rRNA). The timing, magnitude and species composition of the spring bloom varied interannually, with the more Atlantic spring 2014 being distinctly different from the two other years. A strong recurring seasonal pattern was evident in biodiversity, cell abundances and community composition. Winter communities were characterized by high alpha diversity and very low cell numbers with a dominance of heterotrophic and parasitic taxa. Despite large intra- and interannual differences in communities during the productive time of the year, winter communities were always highly similar, suggesting that the polar night represents a strong environmental forcing that resets the microbial communities.

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 score0.069
Threshold uncertainty score0.998

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 studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.210
Teacher spread0.206 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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