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Record W3164809654 · doi:10.1111/anu.13278

Hypoxia does not change responses to dietary omega‐3 long‐chain polyunsaturated fatty acids, but rather reduces dietary energy demand by Atlantic salmon

2021· article· en· W3164809654 on OpenAlexaff
David Huyben, Pedro Muñoz‐Lopez, Bente Ruyter, Brett Glencross

Bibliographic record

VenueAquaculture Nutrition · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Guelph
FundersFiskeri - og havbruksnæringens forskningsfond
KeywordsPolyunsaturated fatty acidBiologyHypoxia (environmental)Food scienceLong chainFatty acidNutrientBiochemistryEndocrinologyInternal medicineChemistryEcologyOxygen

Abstract

fetched live from OpenAlex

Over 116 days, Atlantic salmon postsmolts of 183 ± 5 g were fed diets with high or low levels of lipid (230 or 180 g/kg) with high or low levels of omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA; 14 or 7 g/kg). Fish were reared under hypoxic and normoxic conditions (6.7 or 8.0 mg/L), as an environmental stressor. Higher levels of lipid and n-3 in the diet increased final weight and weight gain, although no lipid x n-3 interaction was found across both environments. Hypoxia led to reduced growth, which can be explained by reduced feed intake, with no effects on FCR being observed. High lipid diets improved protein and energy retention in the fish carcass as well as improved the digestibility of lipid and LC-PUFA, including EPA and DHA. High n-3 diets also improved retention and digestibility of LC-PUFA, and transcriptomic analysis showed that the liver had reduced levels of expression of fatty acid synthesis genes, for example fads2d5 and elovl2 in those treatments. A clear relationship between performance and energy intake, independent of n-3 LC-PUFA intake, shows that energy demand under hypoxia was an over-riding feature of the nutritional responses in this study.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.026
GPT teacher head0.238
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 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

Citations12
Published2021
Admission routes1
Has abstractyes

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