Rapid Communication: A comparison of cardiac lesions and heart weights from market pigs that did and did not die during transport to one Ontario abattoir1
Bibliographic record
Abstract
Abstract In-transit losses of market hogs represent a small proportion of all market-weight pigs shipped in a year. This suggests that individual pig factors may be a significant cause of in-transit losses along with more traditionally considered environmental and transport factors. An investigation was performed to determine whether cardiac pathology and heart weights were associated with pigs that did or did not die during transport to an abattoir. The hearts from 70 pigs that died in-transit to one Ontario abattoir and 388 pigs that arrived alive were collected and examined. Hearts from pigs that died during transport demonstrated greater frequencies of cardiac lesions (P < 0.05). These included hypertrophy of ventricle walls (Left: 97% vs. 64%; Right: 86% vs. 57%), dilation of ventricle chambers (Left: 79% vs. 0.5%; Right: 100% vs. 5%), and dilation of the pulmonary artery and aorta (59% vs. 1.5%). Total heart weight to body weight ratios were increased (3.6 vs. 3.3 g/kg) and left ventricle plus septum weight over right ventricle weight ratio was decreased in pigs that died during transport over non–in-transit loss pigs (2.5 vs. 2.8; P < 0.05). This may indicate reduced cardiac function in hogs that died during transport. Pigs with reduced cardiac function would have exercise intolerance and be more susceptible to death during transport due to the increased cardiac workload required during sorting, loading, and transport of the pigs to the abattoir. Further research to quantify cardiac function in pigs with cardiac lesions or abnormal heart weight ratios is warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".