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Record W2049407265 · doi:10.5539/jas.v2n2p174

In vitro Manipulation of Rumen Fermentation Efficiency by Fumaric acid – Bentonite Coupled Addition as an Alternative to Antibiotics

2010· article· en· W2049407265 on OpenAlexvenueno aff
M. A. Abdl-Rahman

Bibliographic record

VenueJournal of Agricultural Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsFumaric acidRumenFermentationFood scienceChemistryBentoniteAmmoniaFeedlotUreaBiochemistryAnimal scienceBiology

Abstract

fetched live from OpenAlex

Short term in vitro incubations were used to evaluate the effect of fumaric acid - bentonite coupled addition onrumen fermentation effeciency. Ruminal contents from five steers were used for preparation of inoculums ofmixed rumen microorganisms that were used in generatation of three treatment systems, negative control,fumaric acid treated, and fumaric acid – bentonite coupled treated. The fermentation pattern revealed that, thiscoupled addition was associated with an additional increase in propionic acid production and fermentationefficiency and was related to an additional decrease in methanogenesis and VFAs utilization index. Furthermore,it increased total VFAs concentrations and decreased pH value, ammonia nitrogen (NH3–N) concentrations andbutyrate proportions. Meanwhile, it did not alter the proportions of long chain VFAs or cellulase activity.Conclusively, this coupled addition would improve the impact of fumaric acid on rumen fermentation patternand can be appropriate alternative for antibiotic feed additives in improving ruminants feed efficiency.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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

Citations19
Published2010
Admission routes1
Has abstractyes

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