Thromboembolic Conditions, Aetiology Diagnosis and Treatment in Dogs and Cats
Bibliographic record
Abstract
In veterinary medicine, thrombo-embolism (TE) is an under-appreciated medical condition that requires immediate recognition. Since TE is multifactorial and its mode of presentation may vary, veterinarians face great difficulties in making a definitive diagnosis in a timely manner. In addition, most of the underlying conditions that give rise to TE are life-threatening and an aggressive diagnostic and therapeutic approach is required. Not only does the diagnosis and treatment of this condition require the collaboration of many specialties, the costs of therapy can be excessive with a high risk of recurrence. As such, owners have to be thoroughly informed before the therapy commences. While TE has been well-characterized in humans and is associated with significant morbidity and mortality, little information of similar quality is available in veterinary medicine. In addition, TE in animals is distinct from its human counterpart and we cannot simply adapt what is known from human clinical trials. With the promise of improvements in imaging modalities that improve our diagnostic capabilities, the window of opportunity to treat TE increases. This article focuses on aetiology, clinical presentation, diagnosis, and treatment of dogs and cats affected by TE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".