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Record W2796126319 · doi:10.1139/cjas-2017-0012

Effects of diets containing linseed oil or lard and supplemented with pumpkin seeds on oxidative status, blood serum metabolites, growth performance, and meat quality of naked neck chickens

2018· article· en· W2796126319 on OpenAlexvenueno aff
Giorgia Meineri, Erica Longato, Pier Giorgio Peiretti

Bibliographic record

VenueCanadian Journal of Animal Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsPolyunsaturated fatty acidBroilerFood scienceLinseed oilConjugated linoleic acidLinoleic acidChemistryFatty acidAntioxidantBiologyAnimal scienceBiochemistry

Abstract

fetched live from OpenAlex

This study investigates the effect of two dietary fats, namely linseed oil (LO) and lard (LF), and supplementation with pumpkin seeds (PS) on the performance, oxidative status, and blood serum metabolites of broilers, along with the composition, oxidative stability, and fatty acid (FA) profile of broiler meat. Ninety-six 64-d-old naked neck chickens were randomly distributed into four groups of 24 chickens each (8 chickens per cage, three cages per treatment) and fed a LO diet, a LO diet supplemented with 50 g PS kg −1 , a LF diet, and a LF diet supplemented with 50 g PS kg −1 . The antioxidant system is increased and reactive oxygen species decreased in chickens fed PS diets. Glycemia and cholesterol levels were significantly lower in the chickens fed PS diets than in those given diets without supplementation; the cholesterol levels were also significantly lower in the chickens fed LO diets than those fed LF diets. However, the LO diet affected the fresh meat quality by decreasing pH values of the meat at 24 h after slaughter. Adding PS to the LO diet improved the oxidative stability of the muscle at day 3 of refrigerated storage. The use of LO instead of LF favourably modulates the FA profile of meat, by increasing both linoleic and α-linolenic acid content and reducing the n-6/n-3 polyunsaturated FA ratio, atherogenic and thrombogenic index.

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 score0.815
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.240
Teacher spread0.221 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

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