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Record W1972812986 · doi:10.5539/jas.v2n3p183

Effect of Kemzyme - Bentonite Co-supplementation on Cecal Fermentation and Metabolic Pattern in Rabbit

2010· article· en· W1972812986 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRabbits: Nutrition, Reproduction, Health
Canadian institutionsnot available
Fundersnot available
KeywordsFermentationChemistryEnzymeUreaBentoniteFood scienceMetabolismBiochemistryAnimal scienceBiology

Abstract

fetched live from OpenAlex

With the objective of improving the impact of multi-enzymes feed additives on cecal fermentation pattern and rabbit metabolism, sodium bentonite was co-supplemented with “Kemzyme”, a multi-enzyme blend of Kemin Agrifoods Europe. Co-supplementation decreased cecal pH value, increased total VFAs concentration, increased propionates at the expence of acetates and butyrates, increased fermentation efficieny and VFAs utilization. Additionally, co-supplementation increased serum glucose concentration and decreased serum triglycerides and cholesterol concentration. Cecal ammonia nitrogen and serum urea concentration were also decreased by co-supplementation while no change was recorded in serum total proteins concentration. The study therefore, suggested that, coupling bentonite to multi-enzyme feed additives could improve the impact of such enzymes on cecal fermentation pattern and rabbit metablism.

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.

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)0.002
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 score0.644
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.011
GPT teacher head0.280
Teacher spread0.269 · 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