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Influences of temperature, bathymetry and fronts on spawning migration routes of Icelandic capelin (<i>Mallotus villosus</i>)

2012· article· en· W1581361058 on OpenAlexafffund
Anna H. Ólafsdóttir, George A. Rose

Bibliographic record

VenueFisheries Oceanography · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCapelinMallotusOceanographyFisherySpawn (biology)BathymetryGeologyForage fishPredationFish <Actinopterygii>Biology

Abstract

fetched live from OpenAlex

Abstract Capelin ( Mallotus villosus ) is the largest commercial fish stock in Icelandic waters and also an important forage fish. Capelin have adapted to the sub‐arctic environment by migrating north (67–72°N) to feed during summer in deep cold waters (&gt;500 m; 1–3°C) before migrating south (63–65°N) to spawn in winter in warm shallow waters on the south and west coasts of Iceland (&lt;100 m; 5–7°C). Hydroacoustic data on capelin spawning migrations from 1992 to 2007 revealed a consistent southward route along which capelin migrated actively (ground velocity &gt;&gt; current velocity) off the east coast (and a lesser used route off the west coast). North of 65°N, the dominant eastern route followed the bathymetry, skirting the shelf edge (&gt;200 m bottom depth) within a funnel of near constant temperatures (approximately 2.5°C). Further south, between 65 and 64°N, as temperatures warmed to 4.5°C (reaching 7.9°C at 63.5°N), capelin abruptly moved onto the shelf and towards the coastal spawning areas. Capelin spawning migrations appear to be an innately based southward search for appropriate spawning locations, guided by bathymetry and temperature. We suggest that the extended eastern migration route minimizes exposure to cod predation and that warming conditions north of Iceland may result in a northward shift in migrations and spawning locations, as occurred in the 1920s and 1930s.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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

Citations25
Published2012
Admission routes2
Has abstractyes

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