MétaCan
Menu
Back to cohort
Record W1677433098 · doi:10.1111/jpn.12376

Rare earth element‐enriched yeast improved egg production and egg quality in laying hens in the late period of peak egg production

2015· article· en· W1677433098 on OpenAlexaff
C. M. Nyachoti, Joe D Hancock, Jinyoung Lee, Y. H. Kim, D. H. Lee, In Ho Kim

Bibliographic record

VenueJournal of Animal Physiology and Animal Nutrition · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsYolkAnimal scienceBiologyLayingMealFood science

Abstract

fetched live from OpenAlex

The objective of this study was to determine the effects of rare earth element-enriched yeast (RY) on egg production, coefficient of total tract apparent digestibility (CTTAD), egg quality, excreta gas emission and excreta microbiota of laying hens. A total of 216 ISA brown laying hens of 52 weeks of age were used in a 5-week feeding trial and data were collected every week. Birds were randomly allotted to three dietary treatments each with six replicates and 12 hens per replicate. Each cage (38 cm width × 50 cm length × 40 cm height) contained one hen. Treatments consisted of corn-soya bean meal-based diet supplemented with 0, 500 or 1000 mg/kg of RY. From weeks 55 to 56, inclusion of RY linearly increased (p < 0.05) egg production. The CTTAD of nitrogen was increased (linear, p < 0.05) with increasing dietary level of RY. In week 55, yolk height and Haugh units were increased linearly (p < 0.05) with increasing dietary RY content. However, no significant effects were observed in terms of excreta emissions and excreta microbiota in laying hens. In conclusion, dietary supplementation with RY improved egg production and CTTAD of nitrogen and slightly improved egg quality in laying hens of the late period of peak egg production.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.040
GPT teacher head0.275
Teacher spread0.235 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Animal Physiology and Animal NutritionSame topicAnimal Nutrition and PhysiologyFrench-language works237,207