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Record W1756759992 · doi:10.1016/j.aninu.2015.09.003

Effects of dietary threonine:lysine ratioes and sanitary conditions on performance, plasma urea nitrogen, plasma-free threonine and lysine of weaned pigs

2015· article· en· W1756759992 on OpenAlexaff
Balachandar Jayaraman, John K Htoo, C. M. Nyachoti

Bibliographic record

VenueAnimal nutrition · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Manitoba
FundersEvonik Industries
KeywordsLysineThreonineAnimal scienceLimitingMealSoybean mealChemistryPlasma concentrationNitrogenAmino acidBiologyFood scienceBiochemistryEndocrinologySerine

Abstract

fetched live from OpenAlex

Two 21 d-experiments were conducted to determine the optimum standardized ileal digestible (SID) threonine:lysine ratio (Thr:Lys) for weaned piglets reared under clean (Exp. 1) or unclean (Exp. 2) sanitary conditions and fed antibiotic-free diets. In each experiment, 90 mixed-sex pigs (Duroc × [Yorkshire × Landrace]; initial BW 7.2 ± 0.3 kg) were randomly assigned to 5 dietary treatments each with 6 replicates (3 pigs per pen). The dietary treatments were 5 graded levels of SID Thr:Lys (55, 59, 63, 67 and 71%). Diets were corn-wheat-soybean meal-based with a constant SID Lys of 1.18% that was set to be second limiting amino acid. In Exp. 1 and Exp. 2, plasma-free Thr increased (P = 0.05) with increasing dietary SID Thr:Lys. In Exp. 1, the SID Thr:Lys for gain-to-feed ratio (G:F) was optimized at 65%. In Exp. 2, the estimated optimal SID Thr:Lys for overall G:F was 66.5%. In conclusion, an average optimal SID Thr:Lys of 65 and 66.5% could be used to optimize feed efficiency for weaned pigs under clean and unclean sanitary conditions, respectively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.216
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations40
Published2015
Admission routes1
Has abstractyes

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