Breast muscle myopathies: twists and turns in modern broilers
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".