Bibliographic record
Abstract
OBJECTIVE: To present interventional therapeutic options for patients with thrombosis. ETIOLOGY: Thrombosis in small animals results from an unbalance in the normal hemostatic mechanisms leading to vessel occlusion. In veterinary medicine, thrombosis is recognized as a common complication of many acquired diseases, including cardiac, endocrine, immunological, inflammatory, and neoplastic disorders. DIAGNOSIS: Clinical signs are variable depending on the location of the thrombus and various laboratory and imaging modalities can aid in its identification and localization. THERAPY: Once identified, a decision must be made to whether or not intervene and which method is most appropriate. A number of minimally invasive approaches for dealing with thrombosis are available and offer veterinarians a choice of therapeutic options when dealing with a thrombotic patient. In the presence of thrombosis, a combined approach of vessel balloon dilatation, catheter-directed thrombolysis and stenting may be most appropriate. Percutaneous mechanical thrombectomy, if available, may also be appropriate. Embolic trapping devices can be used with vena cava thrombosis to help prevent pulmonary embolism. Anticoagulant therapy may be indicated in the postoperative period to prevent further thrombus formation while the patient's fibrinolytic system breaks the clot down. PROGNOSIS: Outcome is variable depending on the site of the thrombus formation. Arterial thrombosis can be life-threatening while venous thrombosis tends to be less life-threatening but may lead to pulmonary embolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".