Effect of Breed of Sire on Carcass Traits and Meat Quality of Katahdin Lambs
Bibliographic record
Abstract
<span style="font-family: Times New Roman; font-size: small;"> </span><p class="MsoCommentText" style="margin: 0cm 0cm 4pt; text-align: justify; line-height: 12pt; mso-line-height-rule: exactly;"><span style="font-family: Times New Roman; font-size: small;"> </span></p><p>Crossbred lambs (<em>n</em> = 40) of 137 ± 3 days of age from Katahdin ewes with either Charollais (KCh), Dorper (KD), Suffolk (KS) and Texel (KT) sires were used in this study. The effect of sire breeds on carcass traits, chemical composition of muscle, meat quality and consumer acceptability was determined. Regarding carcass traits, KCh animals had the highest fat thickness. KT lambs had the smallest <em>M. Longissimusdorsi</em> (MLD) area compared tothat of KCh, KD and KS (17.0, 15.9, 15.5 and 13.9 cm<sup>2</sup>; respectively). Breed of sire had no effect (<em>P</em>&gt;0.05) on the chemical composition, pH or Warner-Bratzler shear force (WBSF) of lamb; however, it did affect meat color. KS lambs had lower<em> L*, a*, b*</em> and Ch* values compared to the other crossbreeds (<em>P</em>&lt;0.05). Consumer acceptability of lamb was similar (<em>P</em>&gt;0.05) across genotypes.</p><span style="font-family: Times New Roman; font-size: small;"> </span>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".