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Record W4384008581 · doi:10.1016/j.psj.2023.102934

Research Note: Preliminary assessment of the impact of dietary yeast products on egg production and cecal microbial profiles of laying hens

2023· article· en· W4384008581 on OpenAlexafffundabout
D.R. Korver, Si Hong Park, M.K. Costello, Elena G. Olson, J.L. Saunders-Blades, Steven C. Ricke

Bibliographic record

VenuePoultry Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Alberta
FundersAlberta Livestock and Meat AgencyUniversity of Alberta
KeywordsFood scienceLachnospiraceaeLactobacillusBiologyYeastTemperature gradient gel electrophoresisEggshellFermentationAnimal scienceBacteriaEcology16S ribosomal RNABiochemistry

Abstract

fetched live from OpenAlex

The objective of the current study was to conduct an initial comparison of commercial yeast products in layer hen diets on egg production parameters and the corresponding impact on the cecal microbiota. A short-term feeding study was conducted with 35 laying hens receiving either a control, or 1 of 4 different yeast fermentation products, Immunowall, Hilyses (both from ICC, São Paulo, Brazil), Citristim (ADM, Decatur, IL), and Maxi-Gen Plus (CBS Bio Platforms, Calgary, Canada) with 7 hens per treatment from 40 to 46 wk of age. At the end of the trial, hens were euthanized, the ceca removed and prepared for denatured gradient gel electrophoresis (DGGE) microbial compositional analyses. Although initial shell weight and shell thickness were similar among the treatment groups, hens fed Hilyses had lower shell weight and thickness at the end of the experiment. The most predominant DGGE bands with the strongest intensity were identified as Lactobacillus species and excised double bands were identified as Bacillus, Clostridium, or Lachnospiraceae. In this short-term feeding trial, the commercial yeast products tested had little effect on egg production and shell quality, and only moderately impacted the composition of mature layer hen cecal microbiota.

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 score0.852
Threshold uncertainty score0.326

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 studies0.0000.001
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 head0.088
GPT teacher head0.376
Teacher spread0.289 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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