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Record W2118708126 · doi:10.1139/f2012-119

Food restriction prior to release reduces precocious maturity and improves migration tendency of Atlantic salmon (<i>Salmo salar</i>) smolts

2012· article· en· W2118708126 on OpenAlexvenueno aff
Anssi Vainikka, Riina Huusko, Pekka Hyvärinen, Pekka K. Korhonen, Tapio Laaksonen, Juha Koskela, Jouni Vielma, Heikki Hirvonen, Matti Salminen

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersTexas Instruments
KeywordsSalmoJuvenileBiologyFisherySmoltificationAnimal scienceSalmonidaeFish <Actinopterygii>ZoologyEcology

Abstract

fetched live from OpenAlex

Since food availability is known to affect both the precocious maturation and start of feeding migration in wild juvenile salmonids, we examined if a reduction in otherwise plentiful feeding in hatcheries could improve migration tendency and the subsequent survival of released Atlantic salmon (Salmo salar) smolts. A reduction in diet lipid content and feed ration (FR) the previous spring and in FR in the winter prior to release proved efficient; spring-diet treatment halved the proportion of mature males in the autumn prior to release, and a reduction in FR in the winter prior to release decreased latency before leaving the stocking site. In addition, a reduction in FR in winter affected the onset of migration, improved migration speed, and defined the direction of migration downstream in controlled experiments. However, diet manipulations neither affected the swimming endurance nor improved the generally poor tag recapture rates. We conclude that reduced FR at specific times could be used to reduce both precocious male maturity and improve the migration tendency of released 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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

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 head0.012
GPT teacher head0.207
Teacher spread0.195 · 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 designBench or experimental
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

Citations47
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→