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Effects of training on functional variables of muscles in reared Atlantic salmon <i>Salmo salar</i> smolts: connection to downstream migration pattern

2011· article· en· W2089824470 on OpenAlexaff
Katja Anttila, Erkki Jokikokko, Jaakko Erkinaro, M. Järvilehto, Satu Mänttäri

Bibliographic record

VenueJournal of Fish Biology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSalmoBiologyFisherySmoltificationFish <Actinopterygii>Animal scienceZoologySalmonidae

Abstract

fetched live from OpenAlex

The relative amount of muscle contraction regulating dihydropyridine and ryanodine receptors in the swimming muscles of trained reared Atlantic salmon Salmo salar smolts was compared with those of untrained and wild smolts. After an optimized 2 week training period, i.e. swimming with a velocity of 1·5 body lengths per second for 6 h per day, the level of both receptors was significantly higher in the muscles of trained S. salar than in the untrained ones before they were released into the natural environment. This difference persisted after downstream migration in the river. The highest level of receptors was observed in wild S. salar. Swimming performance was also higher in trained fish compared to untrained ones. Furthermore, swimming performance was positively associated with the level of receptors in both red and white muscle types. Downstream migration after release into the wild was significantly slower in trained smolts than in untrained fish. This indicates that trained smolts were most probably swimming harder against the current in the river than untrained smolts. The possible advantages for a slower migration in the river are discussed. This study shows that the prerequisites for effective contraction of the swimming muscles are better met in trained S. salar compared to untrained fish, and the muscles of trained smolts more closely resemble those of wild smolts. The results also imply that the capacity of untrained, reared smolts to swim against the current is not equal to that of their trained or wild counterparts which affects the downstream migration pattern of S. salar smolts.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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

Citations28
Published2011
Admission routes1
Has abstractyes

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