The effect of transport time from the assembly yard to the abattoir and resting time at the abattoir on pork quality
Bibliographic record
Abstract
Over 1900 pigs, supplied by two producers, were first delivered to an assembly yard and then transported to a commercial abattoir. Transport times were 50 min and 2 h, and resting periods at the abattoir were < 30 min, 3 h and 6 h. Times were chosen to represent normal practices in Ontario. The colour and structure of the boneless loins were as sessed subjectively 24 h postmortem. The shorter (50 min) transport time was associated with the highest (P ≤ 0.05) incidence of pale and soft/exudative loins. A longer transport time reduced the incidence of pale and soft/exudative loins; it also increased (P ≤ 0.05) the incidence of dark and firm/dry loins; particularly during winter. A resting period of < 30 min resulted in the highest (P ≤ 0.01) incidence of pale and soft/exudative loins. A 3 h resting period significantly improved (P ≤ 0.01) quality by reducing the incidence of pale loins and soft/exudative loins. Extending the resting period from 3 h to 6 h provided inconsistent improvements in quality due to interactions with season (P ≤ 0.05) and producer/management (P ≤ 0.05). Considering transport time and resting period together further highlighted the importance of resting period at the abattoir. Three h resting period always improved (P ≤ 0.05) quality regardless of transport time, season or producer. Key words: Transport, resting period, pork quality, pale, soft and exudative, DFD
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".