Management of penetrating thoracic wounds from a dog attack in a Nigerian dwarf goat: A case report.
Bibliographic record
Abstract
Pet goat ownership has gradually increased in popularity and veterinarians are expected to provide gold-standard treatments for these animals. As in small-animal practice, decision-making regarding thoracic bite injuries is challenging because of the variability in clinical, radiographic, and surgical findings. Mortality rates from dog bite wounds in small animals range between 15.3 and 17.7%, and these cases represent 10% of all traumatic injuries referred to an emergency service; such information is not available regarding pet goats. The aim of this report is to describe a thoracic dog bite wound in a goat. It details the clinical, radiographic, and surgical findings and the repair, and reports the successful outcome, all to provide information to small-ruminant practitioners for treatment or referral. Future retrospective studies will help to determine prognostic factors for outcomes in goats with thoracic dog bite wounds. Key clinical message: Thoracic bite wounds are a challenge to manage, considering the potential severe underlying pathology and the absence of clear external injuries or clinical signs. Referring veterinarians and owners should be advised that goats with the presence of flail chest, pneumothorax, or rib fractures may require a higher level of intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".