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Record W3006682598 · doi:10.1139/cjas-2019-0064

Effects of dietary <i>Bacillus subtilis</i> RX7 and B2A supplementation on productive performance, egg quality, blood profiles, and excreta <i>Salmonella</i> counts in laying hens

2020· article· en· W3006682598 on OpenAlexvenueno aff
Huan Shi, Wan Lin Zhang, In Ho Kim

Bibliographic record

VenueCanadian Journal of Animal Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
FundersDankook University
KeywordsBacillus subtilisBiologyVirginiamycinAnimal scienceSalmonellaFood sciencePopulationEggshellVeterinary medicineAntibioticsMicrobiologyBacteriaEcology

Abstract

fetched live from OpenAlex

An experiment was carried out to investigate the effect of Bacillus subtilis RX7 and B2A supplementation on egg production, egg quality, blood profile, and excreta Salmonella population in laying hens. A total of 192 Hy-Line Brown laying hens (40-wk-old) were randomly assigned into four dietary treatments, each of which was replicated eight times with six hens per replicate in a 5 wk trial. The dietary treatments were NC, which is a basal diet without antibiotics or Bacillus subtilis; PC, which is an NC + 0.5 g kg−1 antibiotic (virginiamycin) diet; BSR, which is an NC + 0.5 g kg−1 Bacillus subtilis RX7 (1.0 × 109 colony forming units g−1); and BSB, which is an NC + 0.5 g kg−1 Bacillus subtilis B2A (1.0 × 109 colony forming units g−1). The results showed that hens receiving BSB diets had increased (P < 0.05) eggshell thickness over hens fed the NC, PC, and BSR diets (week 3). The excreta Salmonella counts in the PC, BSR, and BSB groups were lower than the NC group (P < 0.05). These results indicate that dietary inclusion of Bacillus subtilis RX7 and B2A strains effectively decreased excreta Salmonella counts without any detrimental effects on the performance of laying hens.

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.240
Teacher spread0.211 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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