Reliability of a White Striping Scoring System and Description of White Striping Prevalence in Purebred Turkey Lines
Bibliographic record
Abstract
To efficiently meet consumer demands for high-quality lean meat, turkeys are selected for increased meat yield, mainly by increasing breast muscle size and growth efficiency. Over time, this has altered muscle morphology and development rates, which are believed to contribute to the prevalence of myopathies. White striping is a myopathy of economic importance which presents as varying degrees of white striations on the surface of skinless breast muscle and can negatively affect consumer acceptance at the point of sale. Breeding for improved meat quality may be a novel strategy for mitigating the development of white striping in turkey meat; however, it is crucial to have a reliable assessment tool before it can be considered as a phenotype. Six observers used a four-category scoring system (0-3) to score severity in several controlled rounds and evaluate intra- and inter-observer reliability of the scoring system. After sufficient inter-observer reliability (Kendall's W > 0.6) was achieved, 12,321 turkey breasts, from four different purebred lines, were scored to assess prevalence of the condition and analyze its relationship with important growth traits. Overall, the prevalence of white striping (Score > 0) was approximately 88% across all genetic lines studied, with most scores being of moderate-severe severity (Score 1 or 2). As was expected, increased white striping severity was associated with higher slaughter weight, breast weight, and breast meat yield (BMY) within each genetic line. This study highlights the importance of training to improve the reliability of a scoring system for white striping in turkeys and was required to provide an updated account on white striping prevalence in modern turkeys. Furthermore, we showed that white striping is an important breast muscle myopathy in turkeys linked to heavily selected traits such as body weight and BMY. White striping should be investigated further as a novel phenotype in future domestic turkey selection through use of a balanced selection index.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".