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Record W2048308304 · doi:10.2527/jas.2007-0702

Conjugated linoleic acid content in adipose tissue of calves suckling beef cows on pasture and supplemented with raw or extruded soybeans1,2

2008· article· en· W2048308304 on OpenAlexaff
Catherine Paradis, R. Berthiaume, C. Lafrenière, R. Gervais, P.Y. Chouinard

Bibliographic record

VenueJournal of Animal Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of GuelphUniversité Laval
Fundersnot available
KeywordsConjugated linoleic acidPastureAdipose tissueChemistryAnimal scienceBeef cattleFood scienceLinoleic acidBiologyAgronomyFatty acidBiochemistry

Abstract

fetched live from OpenAlex

The concentration of CLA in adipose tissue can be increased in ruminants by feeding pasture and extruded soybeans. The objective of this study was to evaluate maternal supplementation of raw (RS) or extruded (ES) soybeans on the concentrations of CLA in milk fat of cows and s.c. adipose tissue of suckling calves. Thirty-two spring-calving cows (BW 624 +/- 76 kg; BCS 3.5 +/- 0.4; mean +/- SD) and calves (BW 127 +/- 15 kg) were separated into 2 groups. Cows were distributed to have 8 calves of each sex in both groups. When animals were turned out to pasture, dams received 2 kg/d of either RS or ES. Dietary treatments had no effect on average milk intake (P = 0.22) and pasture forage intake (P = 0.13) for calves over the course of the grazing season. As a result, no effect of treatments was observed on ADG (P = 0.26). At weaning, milk fat content of CLA reached 15.4 and 24.2 mg/g of total fatty acids for cows fed RS and ES, respectively (P = 0.02). The CLA concentrations in adipose tissue were 16.9 and 25.0 mg/g of total fatty acids for calves suckling dams fed RS and ES, respectively (P < 0.001). Overall, results demonstrated supplementing grazing cows with ES increased CLA content in milk and adipose tissue of suckling calves.

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 score0.664
Threshold uncertainty score0.230

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 studies0.0000.001
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 head0.047
GPT teacher head0.265
Teacher spread0.217 · 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

Citations13
Published2008
Admission routes1
Has abstractyes

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