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Computer simulations of the effects of the Sitka eddy on the migration of sockeye salmon returning to British Columbia

2000· article· en· W2017036024 on OpenAlexaffabout
Healey, Thomson, Leblond, Leonardo Huato, Hinch, Walters

Bibliographic record

VenueFisheries Oceanography · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOncorhynchusMesoscale meteorologyGeologyOceanographyGeographyFisheryFish <Actinopterygii>Biology

Abstract

fetched live from OpenAlex

The Sitka eddy is a mesoscale eddy, 300 km in diameter, that develops off SE Alaska in about one year in two. The eddy has surface currents exceeding 50 km day−1 and it has been suggested that the eddy could deflect migrating salmon to the south, thereby reducing the proportion of British Columbia (BC) sockeye salmon accessible to Alaskan fishers. We modelled its effects on the migration of sockeye salmon (Oncorhynchus nerka) returning to northern BC, using an individual‐based model to simulate migration paths, migration timing and metabolic costs of salmon with different migration behaviours. Except when their migration behaviour included positive rheotaxis, salmon that encountered the eddy had faster migration times and lower metabolic costs than those that did not. The least complex migration behaviour, compass orientation with no rheotaxis, was only slightly less efficient in metabolic terms than the optimal migration paths determined by dynamic programming. Our simulations show that the Sitka eddy itself does not deflect migrating salmon to the south or south‐east regardless of migration behaviour, but that by interrupting the normal northward flow of the Alaskan Current, the eddy could influence latitude of landfall of migrating salmon.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.167
Teacher spread0.164 · 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 designSimulation or modeling
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

Citations21
Published2000
Admission routes2
Has abstractyes

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