Animal welfare in the newborn piglet: a review
Bibliographic record
Abstract
The objective of this review is to integrate clinical findings and laboratory analyses in such a way to improve the welfare of newborn piglets and achieve better prognoses of neonatal viability. Deaths during the intrapartum period account for a significant proportion of pre-weaning mortality in farms worldwide. Piglets which die during parturition generally have normal size and typically lack gross lesions at post-mortem examination. However, circulatory abnormalities in the umbilical cord help in assessing piglet viability. Cord lesions can be classified as normal (adhered), oedematous, congested or haemorrhagic and should always be evaluated in perinatal deaths. The likelihood of neonatal survival decreases rapidly as the severity of umbilical cord lesions increase. The physiometabolic blood profile which includes acid-base balance, degree of dehydration, mineral balance, metabolic expenditure and gas exchange are also useful clinical elements for properly assessing neonatal viability. Neonatal survival is notably reduced when the blood pH falls below 7.0, lactate rises above 90 mg/dl, bicarbonate drops below 10 mmol/l, or the pCO2 increases above 110 mm/Hg. Blood calcium is also an excellent indicator of neonatal stress when used in combination with the other parameters mentioned above. Trembling due to an imbalance in the movement of calcium in muscle is also a factor involved in neonatal mortality. Neurological function in the newborn piglet could also be evaluated by adapting the Apgar score widely used in human perinatology. Neonates with scores lower than 6 in a 10 point scale have generally lower survival rates. The two most important indicators for this vitality score are breathing latency and bradycardia. If the neonate has apnoea for more than 5 min and the cardiac frequency does not increase to more than 110 beats per minute the prognosis for survival is rather poor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".