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Record W2912021226 · doi:10.1139/cjz-2018-0119

Vertical distribution and aggregation patterns of krill (Crustacea: Euphausiacea) in the Bay of Biscay: interannual and seasonal variability

2019· article· en· W2912021226 on OpenAlexvenueno aff
Marian Peña, R. González‐Quirós, I. Munuera-Fernández, Florencio González, Sonia Romero‐Romero, E. Nogueira

Bibliographic record

VenueCanadian Journal of Zoology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsKrillBayEuphausiaceaOceanographyPelagic zoneEuphausiaBiomass (ecology)Antarctic krillCrustaceanFisheryEnvironmental scienceBiologyGeology

Abstract

fetched live from OpenAlex

Studies of krill (Crustacea: Euphausiacea) in oceanic waters of the Bay of Biscay are scarce and restricted to the epipelagic zone, overlooking vertical dynamics such as diurnal vertical migration (DVM). There is a growing interest in acoustically evaluating the biomass of krill in this area, but this requires a good knowledge of its vertical dynamics and aggregation patterns. In this work we employed acoustic data and net samples from two consecutive annual surveys covering a wide off-shelf area of the Bay of Biscay (JUVENA surveys of 2013 and 2014) and four seasonal surveys covering slope and oceanic waters in the Cantabrian Sea (SCAPA surveys of 2015). Vertical dynamics of krill were analyzed in the frame of the environmental seascape. High interannual and seasonal variations in the vertical distribution and aggregation patterns (small swarms, dense aggregations, or loose layers) of krill were observed. The vertical distribution covaried with dissolved oxygen and salinity. According to our findings, the best season to acoustically evaluate krill in the Bay of Biscay is spring, with the bulk of the biomass located above 600 m depth. Moreover, extending the acoustic recording beyond the epipelagic zone is mandatory for any season.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.145
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.218
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2019
Admission routes1
Has abstractyes

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