A retrospective study of brain lesions in goats submitted to three veterinary diagnostic laboratories
Bibliographic record
Abstract
A retrospective study of brain lesions in goats was conducted to identify the range of lesions and diseases recognized and to make recommendations regarding the best tissues to examine and tests to conduct in order to maximize the likelihood of making a definitive diagnosis in goats that may have had clinical signs referable to the brain. One hundred thirty-nine goats with a brain lesion were identified. The most common lesion, in 52.5% of the goats, was suppurative inflammation. Approximately two-thirds of these goats had encephalitic listeriosis. Other goats were found to have suppurative inflammation in association with septicemia, pituitary abscesses, dehorning injury, and otitis. Thirty goats (21.6%) were diagnosed with polioencephalomalacia. Twenty-one goats (15.1%) were diagnosed with nonsuppurative inflammation. In more than half of these goats, no definitive diagnosis was made, while 8 were infected with Caprine arthritis encephalitis virus and 1 with Rabies virus. However, few goats were tested for rabies. Based on these findings, it is recommended that, in addition to appropriate handling of the brain, the head should be examined with attention paid to the sella turcica and the temporal bones for evidence of a pituitary abscess and otitis, respectively. Histologic examination should include multiple areas of the brain, including the brainstem, for lesions of encephalic listeriosis; the cerebral cortex, for lesions of polioencephalomalacia; and the hippocampus, for Negri bodies associated with Rabies virus infection. Consideration should be given to collecting samples of other tissues including, but not limited to, the spinal cord and liver for ancillary testing if 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".