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Record W4415099667 · doi:10.1016/j.japr.2025.100616

Informal nutrition symposium: Overview of the nutrient requirements of poultry, 10th revised edition

2025· article· en· W4415099667 on OpenAlexaff
K. C. Klasing, W.A. Dozier, Gonzalo González Mateos, M.E. Persia, Rosemary L. Walzem, Nilva Kazue Sakomura, Matheus de Paula Reis, Gabriel da Silva Viana, Rony Riveros Lizana, Robert G. Elkin, R. Angel, D.R. Korver

Bibliographic record

VenueThe Journal of Applied Poultry Research · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWork (physics)NutrientIdentification (biology)Family and consumer scienceResearch council

Abstract

fetched live from OpenAlex

The most recent (9th) edition of the National Research Council’s “Nutrient Requirement of Poultry” report was published in 1994. A new edition of this report is being prepared for release in 2025, by the National Academies of Science, Engineering and Medicine (NASEM). The 10th edition of the Nutrient Requirements of Poultry publication is substantially updated in terms of the volume of information included, reflecting the goal to serve a more educational purpose than previous reports. Wherever possible, nutrient requirement values have been updated to reflect the most current research. However, for many of the individual nutrients, little work has been done to determine the requirements of modern poultry strains. A preview of the updated NASEM report was presented during the Informal Nutrition Symposium at the 2024 Annual Meeting of the Poultry Science Association. Topics included overviews of each chapter, as well as identification of the substantial research gaps for most nutrients, and a discussion of the use and need for mathematical models to allow for prediction of nutrient requirements of the ever-changing genetics of commercial poultry.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.190

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 communication0.0000.000
Open science0.0010.000
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 head0.094
GPT teacher head0.357
Teacher spread0.263 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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