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Record W4416307598 · doi:10.1155/anu/4044914

Balancing Dietary Vitamin D <sub>3</sub> and Phosphorus Improved Growth, Mineralization, and Fecal Characteristics of Atlantic Salmon ( <i>Salmo salar</i> ) Post‐Smolts in Land‐Based Aquaculture

2025· article· en· W4416307598 on OpenAlexaff
Vegard Øvstetun Flo, Jon Øvrum Hansen, Christopher Hawes, Tomé S. Silva, Alasdair Currie, Jannicke Vigen, Odd-Ivar Lekang

Bibliographic record

VenueAquaculture Nutrition · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsCargill (Canada)
FundersNorges Forskningsråd
KeywordsVitaminAquacultureVitamin D and neurologyPhosphorusFactorial experimentNutrientFecesMineralization (soil science)

Abstract

fetched live from OpenAlex

Metabolic responses to different dietary levels of vitamin D 3 and available phosphorus (avP) was investigated in cultured Atlantic salmon ( Salmo salar ). The study was carried out in triplicate with a 2‐level full factorial design with a center point and three additional points within the design space. Over a 17‐ week period at the initial weight of 453 ± 9 g, salmon reared indoor on land, were fed diets containing different levels of vitamin D 3 and avP. In summary,growth performance, measured as specific growth rate (SGR), improved when either vitamin D 3 or avP was increased independently, but declined when both were elevated excessively. Bone mineralization was maintained at intermediate vitamin D 3 inclusion levels, though high vitamin D 3 reduced bone ash. A diet containing 0.63 mg/kg vitamin D 3 and 0.70% avP supported growth and mineral retention. A significant reduction in fecal soluble phosphorus when vitamin D 3 was increased in the diet, suggests that management of vitamin D 3 can contribute to improved waste control and reduced environmental load for phosphorus. Finally, the study highlighted that today’s commercial dietary inclusion of vitamin D 3 can result in lower vitamin D 3 accumulation in muscle of land‐based farmed Atlantic salmon compared to wild Atlantic 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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.006
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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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