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Record W4412406944 · doi:10.1080/03079457.2025.2533454

Breast muscle myopathies: twists and turns in modern broilers

2025· review· en· W4412406944 on OpenAlexaff
Elizabeth S. Greene, Sunoh Che, Francesca Soglia, Tomohito Iwasaki, Takafumi Watanabe, Takeshi Kawasaki, Leonardo Susta, Massimiliano Petracci, Colin G. Scanes, Sami Dridi

Bibliographic record

VenueAvian Pathology · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Guelph
FundersJapan Society for the Promotion of ScienceU.S. Department of Agriculture
KeywordsBiologyBroilerAnatomyAnimal science

Abstract

fetched live from OpenAlex

Although poultry meat production supports the livelihood and provides food security for billions of people worldwide, it is facing substantial challenges. The emergence of broiler breast myopathies (white striping, woody breast, spaghetti meat) at large scale is one of the most significant economic and welfare challenges that menace poultry production sustainability and for which there is currently no effective prevention, due to its unknown aetiologies. Here, by inviting and gathering several experts with diverse, but complementary disciplines, the objective of the present review is to highlight the current progress and knowledge on these myopathies. Five sections are presented, describing in detail the history and geographic occurrence of these breast myopathies, their macroscopic morphologies and microscopic characteristics, their putative aetiologies and causes as well as their underlying molecular mechanisms, and potential strategies and solutions. The is review summarizes both descriptive and functional mechanistic studies, highlights the complexity of these myopathies and the kinship between broiler genome, nutrition, and management, and outlines some of the promising molecular signatures. It aims to offer new fundamental frameworks for future investigations.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.025
GPT teacher head0.267
Teacher spread0.243 · 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 designOther design
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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