Tongue lesions in feedlot cattle associated with ergot alkaloid consumption.
Bibliographic record
Abstract
Over 1200 heavy feedlot cattle presented with severe tongue lesions during a 7-month interval. Review of the literature and discussions with colleagues revealed previous similar outbreaks had occurred in Canada and the USA, with extensive investigations conducted and no cause identified. In the current outbreak, examination of the environment, feed, water, cattle behavior, and husbandry systems were conducted, as well as diagnostic testing including necropsy, histopathology, bacteriology, virology, and toxicology. All the initial testing to determine the cause of the lesions was unrewarding. As cases continued and increased during the second month, a further inspection of feedstuffs was undertaken. Hard clumps were identified in the dried distiller's grains with solubles feed additive (DDGS), and samples were submitted for additional mycotoxin analysis. Toxic concentrations of ergot alkaloids were detected, leading to a presumptive diagnosis of localised ergot toxicosis. Removal of the affected DDGS from the diet led to a decrease and eventual cessation of cases. This case report highlights the value of extensive collaborations among onsite and offsite colleagues when conducting detailed investigations on farm of a diagnostically challenging case. Key clinical message: This report describes a large outbreak of tongue lesions in feedlot cattle associated with ergot toxicosis. The report highlights the extensive investigation with collaboration among the producer, veterinarians, laboratory teams, and colleagues from further afield. Toxic concentrations of ergot alkaloids were present in hard clumps in the dried distiller's grains with solubles feed additive (DDGS), suggesting a possible etiology of localized ergot toxicosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".