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Record W2175034729 · doi:10.4141/cjas-2014-019

Short Communication: Assessment of lemongrass oil supplementation in a dairy diet on in vitro ruminal fermentation characteristics using the rumen simulation technique

2014· article· en· W2175034729 on OpenAlexafffundvenue
Atitthan Nanon, Wisitiporn Suksombat, K. A. Beauchemin, Weijuan Yang

Bibliographic record

VenueCanadian Journal of Animal Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaRoyal Golden Jubilee (RGJ) Ph.D. ProgrammeThailand Research FundSuranaree University of Technology
KeywordsRumenDry matterFermentationFood scienceTotal mixed rationAnimal scienceChemistryDairy cattleBiologyLactation

Abstract

fetched live from OpenAlex

Nanon, A., Suksombat, W., Beauchemin, K. A. and Yang, W. Z. 2014. Short Communication: Assessment of lemongrass oil supplementation in a dairy diet on in vitro ruminal fermentation characteristics using the rumen simulation technique. Can. J. Anim. Sci. 94: 731–736. A study using a rumen simulation technique (Rusitec) was conducted to investigate the effect of increasing lemongrass oil (LMO) supplementation on ruminal fermentation characteristics of a dairy cow diet. Increasing LMO from 0, to 100 to 200 mg kg −1 dry matter did not affect volatile fatty acid concentration, whereas LMO supplementation increased large and small peptide N and reduced ammonia N concentration. Adding 200 mg of LMO kg −1 dry matter also increased microbial N production. However, feed digestibility was not affected by LMO supplementation. These results suggest that the addition of LMO may inhibit deamination in the rumen.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.322
Teacher spread0.280 · 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 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

Citations18
Published2014
Admission routes3
Has abstractyes

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