MétaCan
Menu
Back to cohort
Record W2479012736 · doi:10.1139/cjas-2015-0198

Effects of xylanase supplementation on growth performance, digestibility, fecal gas emission, and meat quality in growing-finishing pigs

2016· article· en· W2479012736 on OpenAlexvenueno aff
Jin Ho Cho, J.H. Park, JM Lee, Tae-Hwa Song, In Ho Kim

Bibliographic record

VenueCanadian Journal of Animal Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsXylanaseDry matterFecesCrossbreedAnimal scienceChemistryFood scienceBiologyBiochemistryEnzyme

Abstract

fetched live from OpenAlex

A total of 144 crossbred pigs [(Landrace × Yorkshire) × Duroc] with an initial body weight (BW) of 25.7 ± 2.3 kg were used in a 16-wk study to evaluate the effects of xylanase supplementation in growing–finishing pigs. Treatments were as follows: control diet (CON); low-energy diet (LX) + 0.01% xylanase; and alternative diet (AX) + 0.01% xylanase. From weeks 0 to 6, pigs in the AX treatment had greater (P < 0.05) average daily feed intake (ADFI) than those in the CON treatment. On the sixth week, higher (P < 0.05) apparent total tract digestibility (ATTD) of energy was observed in the AX treatment compared with the CON treatment. Pigs fed the AX diet had the lowest (P < 0.05) ATTD of energy among all of the treatments on week 12. At the end of the experiment, the ATTD of dry matter (DM) of pigs in the LX treatment was higher (P < 0.05) than those in the AX and CON treatments. The redness values in the LX and AX treatments were higher (P < 0.05) than that in the CON treatment. In conclusion, our results indicated that dietary inclusion of 0.01% xylanase supplement could improve ADFI during weeks 0–6, ATTD of DM at week 16 and energy at weeks 6 and 12, and the redness color of meat in growing–finishing 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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.022
GPT teacher head0.259
Teacher spread0.237 · 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 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

Citations7
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Animal ScienceSame topicAnimal Nutrition and PhysiologyFrench-language works237,207