Bibliographic record
Abstract
A 7 year-old female spayed Maltese mixed breed dog was referred to the Emergency Service at the Cornell University Hospital for Animals for acute onset paraplegia. The patient had seen the referring veterinarian shortly after clinical signs began and a presumptive diagnosis of intervertebral disc disease was made; the patient was referred to Cornell for further evaluation. On presentation to the Emergency Service, the patient was paraplegic, but deep pain sensation remained intact. Absent femoral pulses were noted bilaterally and the hind paws were cool to the touch when compared to the front paws. Blood pressure was unmeasurable in both pelvic limbs, but was normal in the thoracic limbs. These findings, coupled with a brief, point of care echocardiogram that showed a mass lesion (suspected thrombus) within the left ventricle, were highly suggestive of an aortic thromboembolism. Serial bloodwork, a urinalysis, blood and urine cultures, serial abdominal ultrasounds, an echocardiogram, thoracic radiographs, and a thromboelastogram were supportive of an aortic thromboembolism. The dog was hospitalized for 6 days with slight improvement and discharged on anti-coagulant therapy, broad-spectrum antibiotics, and pain control. Several recheck examinations showed improving motor function, increasingly palpable femoral pulses, as well as dissipation of the presumptive left ventricular thrombus. This report will describe the pertinent clinical findings, diagnostics and treatment in a dog with an aortic thromboembolism.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".