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Record W2917330203 · doi:10.1139/cjas-2018-0166

The effects of microencapsulated compounds supplementation on growth performance, immune cells, and rectal temperature in weaned pigs by lipopolysaccharides

2019· article· en· W2917330203 on OpenAlexvenueno aff
Woo Gi Kwak, Minho Song, Dong Hoon Lee, Won Yun, Ji Hwan Lee, Changhee Lee, Han Jin Oh, Shudong Liu, Ji Seon An, Hyeun Bum Kim, Jin Ho Cho

Bibliographic record

VenueCanadian Journal of Animal Science · 2019
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsnot available
Fundersnot available
KeywordsImmune systemRectal temperatureAnimal scienceFood scienceBiologyChemistryImmunology

Abstract

fetched live from OpenAlex

A total of forty 21-d-old weaned and crossbred pigs [(Landrace × Yorkshire) × Duroc] with an average initial body weight of 4.43 ± 1.41 kg were used for this 2 wk experiment. There were four treatments. Each treatment had 10 replicates with five pigs per pen. Treatments were as follows: (1) microencapsulated complex of organic acids and essential oils (MOE)−, lipopolysaccharide (LPS)+; (2) MOE−, LPS−; (3) 0.2% MOE+, LPS+; and (4) 0.2% MOE+, LPS−. Final body weight, body weight gain, average daily gain, and average daily feed intake were significantly different between MOE+ and MOE− (P < 0.05). Based on the results of MOE+, crude protein digestibility was significantly higher than for MOE− (P < 0.05). However, LPS+ was significantly higher than LPS− in the 4, 8, 12, and 16 h (P < 0.05). From a comparison of blood profiles, cortisol, tumor necrosis factor-α, interleukin-1β, neutrophil, lymphocyte, red blood cell, hemoglobin, and hematocrit were significantly different between LPS+ and LPS− (P < 0.05). The immunoglobulin G, white blood cell, and eosinophil were significantly different between LPS and MOE treatments (P < 0.05). In summary, MOE had a potentially good effect on growth performance and some part of immune response in weaned pigs.

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 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 score0.116
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.003
GPT teacher head0.216
Teacher spread0.213 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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