Suspected fenugreek ( <i>Trigonella foenum-graecum</i> L.) toxicosis in a herd of Saskatchewan beef cattle
Bibliographic record
Abstract
An apparent outbreak of fenugreek forage toxicosis occurred in a beef cattle herd near Moose Jaw, Saskatchewan in February-May 2022. The herd had consumed fenugreek hay from late fall to early winter. Clinical signs included various degrees of weakness, ataxia, knuckling, walking on hocks, and recumbency. All adult cattle in the herd eventually died or were euthanized. Feed analysis did not reveal nutritional deficiencies or mycotoxin contamination. Liver mineral and vitamin status of affected animals did not indicate any consistent abnormality. The last live cow in the herd was presented to a veterinary teaching hospital for evaluation and subsequent postmortem examination. Major postmortem findings included emaciation, and sciatic nerve and spinal cord axonal degeneration. Histologic examination of the sciatic nerve showed Wallerian-like axonal degeneration, increased Schwann cell nuclei, and endoneurial fibrosis. Histologic examination of the spinal cord showed infrequent myelin sheath dilation and digestion chambers within white matter. These results are consistent with other reports of natural and experimental outbreaks of fenugreek poisoning in livestock. To our knowledge, fenugreek toxicosis has not been reported previously in Canada. We conclude that caution should be taken when feeding fenugreek hay to cattle.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".