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Fatty Acids in the Meat of Buffaloes Supplemented with Fish Oil

2013· article· en· W1991966736 on OpenAlexvenueno aff
J. F. Cedrés, María Alicia Judis, M. Sánchez Negrette, Ana Romero, Mirtha Marina Doval, G. Crudeli

Bibliographic record

VenueJournal of Buffalo Science · 2013
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
FundersAgencia Nacional de Promoción Científica y TecnológicaUniversidad Nacional del Nordeste
KeywordsIntramuscular fatFood scienceFish oilConjugated linoleic acidSunflower oilLinoleic acidChemistryFatty acidBiologyAnimal scienceFish <Actinopterygii>Biochemistry

Abstract

fetched live from OpenAlex

The purpose of this study has been to investigate the influence of both a supplementary fish oil diet on conjugated linoleic acid (CLA) and n6 and n3 fatty acids on intramuscular fat in Mediterranean buffalo meat. Twenty animals were randomly divided into two groups and fed with Brachiaria brizantha, 3Kg rice bran, 500 g corn and 500 g sunflower pellets for 60 days. Group I received this diet only while in group II each animal received additional 100 ml fish oil daily. Results indicated a significant decrease of palmitic fatty acid in group II (232.67 mg/g fat) in relation to group I (254.73 mg/g fat). Among unsaturated acids (AGI), the 9c 11t CLA value of group II (21.23 mg/g fat) showed an increase in relation to group I (15.80 mg/g fat), while the linoleic acid content of group II (28,85 mg/g fat) decreased significantly in relation to group I (47,00 mg/g fat). However, the alpha linolenic acid showed no significant difference between the supplemented diet group and the control group (10.31 and 10.70 mg/g fat, respectively). Group II n6/n3 ratio was narrower (2.69:1) than that of group I (4.55:1). Summing up, group II diet, which included fish oil, increased the CLA content in intramuscular fat and decreased the n6 fatty acids, improving the n6/n3 ratio.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.025
GPT teacher head0.315
Teacher spread0.290 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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