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Record W2020125154 · doi:10.1080/00039420214185

Effects of Feeding Pigs Increasing Levels of C 18:1<i>Trans</i>Fatty Acids on Fatty Acid Composition of Backfat and Intramuscular Fat as well as Backfat Firmness

2002· article· en· W2020125154 on OpenAlexaff
Karola R. Gläser, C. Wenk, M.R.L. Scheeder

Bibliographic record

VenueArchiv für Tierernaehrung · 2002
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsConjugated linoleic acidChemistryVaccenic acidSunflower oilLinoleic acidFatty acidFood scienceOleic acidComposition (language)Polyunsaturated fatty acidBioconversionAdipose tissueBiochemistry

Abstract

fetched live from OpenAlex

Forty Large White pigs were fed from 30 kg to 103 kg body mass on diets supplemented with 6% of pure high-oleic sunflower oil (HO) or HO plus increasing amounts of partially hydrogenated rape seed oil (HR; 1.85%, 3.70%, 5.55%), containing high levels of delta 6 to delta 11 C 18:1 trans fatty acid isomers. Increasing dietary C 18: trans fatty acids resulted in a linear increase in C 18:1 trans fatty acids and conjugated linoleic acid (cis-9, trans-11 CLA) in backfat (BF) as well as in neutral lipids (NL) and phospholipids (PL) of M. long. dorsi. Thus, the rate of bioconversion of trans vaccenic acid (TVA) into CLA and incorporation of C 18:1 trans and CLA into pig adipose tissue was not limited up to 25 g total C 18:1 trans fatty acids including 3.3 g of TVA per kg feed. BF was higher in C 18:1 trans fatty acids and CLA than M. long. dorsi NL and PL. In BF and NL the sum of saturated fatty acids (SFA) increased with increasing dietary amounts of HR, while in PL SFA were reduced. Thus, according to their physical properties, C 18:1 trans fatty acids partly replaced SFA in PL. Firmness of backfat was also significantly increased (P < 0.05) with increasing amounts of HR in feed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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.

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

Citations35
Published2002
Admission routes1
Has abstractyes

Explore more

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