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Record W2145009373 · doi:10.1139/f07-135

Vertical migration in adult Atlantic cod (<i>Gadus morhua</i>)

2007· article· en· W2145009373 on OpenAlexvenueno aff
Espen Strand, Geir Huse

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNorges ForskningsrådEuropean Commission
KeywordsPelagic zoneGadusPredationBenthic zoneDiel vertical migrationAtlantic codOceanographyFisheryGadidaeZooplanktonBiologyEnvironmental scienceEcologyGeologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

We investigate the trade-offs associated with vertical migration and swimming speed of Atlantic cod (Gadus morhua) using an adaptive individual-based model. Simulations with varying distribution and occurrence of prey, with and without swimbladder constraints, and visual predation were performed. Most simulations resulted in cod migrations between the bottom and pelagic zones. In simulations with high probability of encountering pelagic prey, the cod spent the daytime in the pelagic zone, moving to the bottom to feed only when no pelagic prey were encountered. At night the cod stayed in the pelagic zone to attain neutral buoyancy. In simulations with low occurrence of pelagic prey or high visual predation pressure, the cod remained at the bottom feeding on the consistently present benthic prey. If the pelagic prey occurred far above the sea floor or there were no benthic prey, the cod abandoned all bottom contact. The study thus predicts that the probability of encountering energy-rich pelagic prey is the key factor in driving vertical migration in adult cod. Buoyancy regulation is further shown to be an important constraint on vertical migration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.015
GPT teacher head0.233
Teacher spread0.217 · 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

Citations35
Published2007
Admission routes1
Has abstractyes

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