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Juvenile growth and aggression in diploid and triploid Chinook salmon <i>Oncorhynchus tshawytscha </i>(Walbaum)

2008· article· en· W2077150791 on OpenAlexaff
Shawn R. Garner, Barry N. Madison, Nicholas J. Bernier, Bryan D. Neff

Bibliographic record

VenueJournal of Fish Biology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of GuelphWestern University
Fundersnot available
KeywordsBiologyChinook windPloidyOncorhynchusJuvenileAquacultureAnimal scienceZoologyFisheryFish <Actinopterygii>GeneticsGene

Abstract

fetched live from OpenAlex

Multilocus heterozygosity, aggressive and feeding behaviour, plasma cortisol levels and growth rate were evaluated among three groups of juvenile Chinook salmon Oncorhynchus tshawytscha : diploid, triploid and mixed groups of diploid and triploid fish. There was no difference between diploid and triploid fish in measurements of heterozygosity calculated using seven microsatellite loci, and these measurements did not correlate with performance measurements including feeding rate and growth rate. Aggression trials that examined small groups of fish revealed that after 4 days together in tanks, triploid fish were significantly less aggressive during feeding than diploid fish or fish in mixed groups. At the end of the trials, however, plasma cortisol levels did not differ among the three groups. Thirty‐day growth trials in duplicate tanks of 60 fish revealed no difference in growth rate among diploid, triploid and mixed groups, but plasma cortisol levels were significantly lower in triploid fish than in either diploid fish or the mixed fish. Overall, independent of the above differences in aggressive behaviour and cortisol levels, these results suggest similar performance in diploid and triploid Chinook salmon, and thus provide support for the viability of triploid Chinook salmon culture in commercial aquaculture.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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.

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

Citations43
Published2008
Admission routes1
Has abstractyes

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