Effects of transport time and location within truck on skin bruises and meat quality of market weight pigs in two seasons
Bibliographic record
Abstract
Scheeren, M. B., Gonyou, H. W., Brown, J., Weschenfelder, A. V. and Faucitano, L. 2014. Effects of transport time and location within truck on skin bruises and meat quality of market weight pigs in two seasons. Can. J. Anim. Sci. 94: 71–78. The effects of season (winter vs. summer), transport time (T: 6, 12 and 18 h) and truck compartment (C) on skin bruise score and meat quality were evaluated in 384 pigs distributed across the top front (C1), top back (C4), middle front (C5) and bottom rear (C10) compartments. Bruise score was higher (P=0.01) in winter than in summer. A T×C interaction was found for pH u value in the longissimus thoracis (LT) muscle and for drip loss in the LT and semimembranosus (SM) muscles, with higher (P<0.001) pH u being recorded in the LT muscle and lower drip loss in the LT and SM muscles (P<0.001 and P=0.01, respectively) of pigs located in C10 following 18 h of transport. In summer, higher (P=0.03) pH u values were found in the LT muscle of pigs transported in C4 and lower drip loss in the LT and SM muscles (P=0.04 and P=0.03, respectively) of pigs located in C10. The results of this study suggest that, while skin bruises are only affected by season, the effects of longer transport time and winter temperatures on meat quality can be aggravated by the compartment location.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Animal science study of pig transport conditions and meat quality.
This studies pig transport conditions and meat quality, not research itself.
Animal science study of pig transport effects on bruises and meat quality.
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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".