Associations of melanocortin 1 receptor genotype with growth and carcass traits in beef cattle
Bibliographic record
Abstract
Melanocortin 1 Receptor (MC1R) is considered to be the main gene controlling the production of eumelanin or phaeomelanin, resulting in black or red coat colour of cattle. The recessive red allele, e, codes for a nonfunctional receptor, which does not bind the agonist alpha-melanocyte stimulating hormone (α-MSH), allowing for the production of phaeomelanin, or red pigment, whereas the dominant ED allele binds α-MSH leading to the production of eumelanin. We hypothesized that black cattle would have more α-MSH bound to MC1R, which could result in more α-MSH binding to the appetite suppressing receptor, Melanocortin 4 Receptor. We genotyped 328 crossbred steers of various colours that were purchased at weaning and fed until slaughter. Black cattle of ED/ED or ED/e genotype had increased back fat and required significantly fewer days (15-25) on feed to reach a target fat level for slaughter than the red cattle. Red cattle of e/e genotype were found to have a significantly larger longissimus dorsi (l. dorsi), shipping weight and hot carcass weight. Differences were comparable whether black versus red coat colour or MC1R genotype were used as the criteria for the group of cattle. Key words: Coat colour, MC4R, MC1R, α-MSH, shipping weight
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".