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Record W2796585643 · doi:10.14943/bull.fish.70.1.91

Comparison of the vertical distribution of pelagic copepod abundance, biomass and community structure between the Atlantic and Pacific sectors of the Arctic Ocean

2018· article· en· W2796585643 on OpenAlexaboutno aff
Yoshiyuki Abe, Nicole Hildebrandt, Kohei Matsuno, Barbara Niehoff, Atsushi Yamaguchi

Bibliographic record

VenueHokkaido University Collection of Scholarly and Academic Papers (Hokkaido University) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersJST-Mirai ProgramJapan Society for the Promotion of Science
KeywordsPelagic zoneOceanographyArcticSea iceCopepodArctic dipole anomalyArctic ice packEnvironmental scienceBiomass (ecology)PlanktonFisheryGeographyGeologyDrift iceBiologyCrustacean

Abstract

fetched live from OpenAlex

We compared copepod abundance, biomass and community structure in the Atlantic sector (Fram Strait) and Pacific sector (Canada Basin) of the Arctic Ocean by using vertical stratified zooplankton samples collected from 0-1,000 m or 0-1,500 m during daytime in summer. Abundance and biomass were high at the surface layer and decreased with increasing depth in both regions. Abundance and biomass in the surface layer in the Fram Strait were 6-18 times higher than those in the Canada Basin. \nAccording to cluster analysis, the copepod communities were separated into three groups that varied vertically and included both locations. Regional differences were marked for Calanus finmarchicus, which was distributed only in the Fram Strait. In the Canada Basin, Spinocalanidae composed 56.1% of calanoid copepod abundance for the bathypelagic groups and also contributed 7.5% of abundance throughout the water column. The dominance of Spinocalanidae may reflect the oligotrophic environment in the Pacific sector of the Arctic Ocean.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.017
GPT teacher head0.224
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

Citations0
Published2018
Admission routes1
Has abstractyes

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