Evaluation of blood metabolites reflects presence or absence of liver abscesses in beef cattle
Bibliographic record
Abstract
Liver abscesses constitute a prominent concern regarding animal health and profitability of the beef industry. Our objective was to evaluate potential biliary and blood indicators of liver abscesses. Twenty-nine beef bulls (initially averaging 356±70.5 kg and 253±30 days of age) were fed a high-concentrate diet during a performance test of 112 days, during which blood was collected at nine time points spaced 0.5-13 days apart within 56 days before slaughter. At the abattoir, blood and bile were collected and livers were inspected for liver abscesses. Results indicated that liver abscesses are associated with elevated levels of plasma cortisol and aspartate aminotransferase, and decreased levels of albumin, cholesterol and testosterone over the period before slaughter. Based on the blood samples collected during exsanguination, the presence of liver abscesses was associated with lower concentrations of thyroxine, albumin, cholesterol and alkaline phosphatase, and is suggested to be associated with lower blood carbon dioxide (P=0.08) and lower biliary cortisol metabolites (P=0.07). Albumin and cholesterol are established indicators of hepatic function and are consistently related to the presence of liver abscesses. Identifying blood parameters that predict liver abscesses has practical implications for cattle husbandry and for ensuring food safety.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".