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Record W4409359856 · doi:10.1139/cjfas-2024-0103

Wild juvenile Atlantic salmon (Salmo salar) offer insights into movement patterns of territorial freshwater fishes in relation to high temperature and proximity to thermal refuges

2025· article· en· W4409359856 on OpenAlexaffvenue
Emily Corey, Tommi Linnansaari, Antóin M. O’Sullivan, R. Allen Curry, Richard A. Cunjak

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSalmoJuvenileFisheryBiologyEcologySalmonidaeFish <Actinopterygii>Zoology

Abstract

fetched live from OpenAlex

When exposed to increased water temperatures, salmonids abandon territories and relocate to areas of cool water (thermal refuges). Using juvenile Atlantic salmon (Salmo salar) as a model species, our study, conducted over two seasons (2009 and 2010) with 636 salmon parr tagged by Passive Integrated Transponder (PIT) across 9 km of the Little Southwest Miramichi river, investigated the effects of high temperature stress on their movement. We aimed to determine the extent of their travel to thermal refuges, primary direction, duration within these refuges, and post-event redistribution. In 2009, despite temperatures peaking at 26.1˚C, no significant parr aggregations were noted. However, 2010 experienced notable changes: temperatures exceeding 27.3˚C for four days prompted 32.7% of the parr to form aggregations, with movements significantly greater than in 2009 (p < 0.001), peaking at 7.4 km. Most migrations were localized within specific river reaches. By late fall, 92.3% of parr returned to or near their original tagging locations. These observations underscore the importance of thermal refuges and the adaptive strategies juvenile salmon employ during extreme temperature events.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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
Published2025
Admission routes2
Has abstractyes

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