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Record W4397021998 · doi:10.1093/plankt/fbae022

Living at depth: ecophysiological condition of <i>Boreomysis arctica</i> in autumn and winter in the St. Lawrence estuary and gulf

2024· article· en· W4397021998 on OpenAlexafffund
Gesche Winkler, Jory Cabrol, Réjean Tremblay

Bibliographic record

VenueJournal of Plankton Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsFisheries and Oceans CanadaUniversité du Québec à Rimouski
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEstuaryOceanographyGeographyEnvironmental scienceClimatologyGeology

Abstract

fetched live from OpenAlex

Abstract Mysids, besides krill, play a significant role in energy transfer and carbon sequestration. The ecology of coastal species is better understood than that of deep dwelling species such as Boreomysis arctica. The objectives of this study were to quantify spatiotemporal variations in body condition and the trophic level of B. arctica in autumn and winter, under sea-ice conditions in the St. Lawrence system, using a multimarker approach. We sampled along a 1000 km transect. Mean abundances in winter were higher in the estuary compared to the Gulf of St. Lawrence. Body condition, measured as total lipid content, was higher in winter than in autumn. Lipids of B. arctica were mainly composed of wax esters, thereby B. arctica is richer in energetic lipids compared to the three dominant krill species. We also observed seasonal differences in the trophic level of B. arctica, revealing carnivorous behavior in autumn compared to omnivory in winter. High intra-specific variability in both energetic strategy and feeding behavior was found that is potentially due to opportunistic feeding. Energy rich reserves suggest that B. arctica could act as a valuable prey for both benthic and pelagic consumers and thus playing a key role in bentho-pelagic energy transfer.

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)0.000
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 score0.916
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.334
Teacher spread0.302 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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