Use of intraoperative ultrasound aiding in extraction of migrated and embedded porcupine quills in a dog
Bibliographic record
Abstract
Abstract A dog presented for porcupine quills; the client had removed the majority of quills themselves, but due to recurring quills and progressive swelling of the left thoracic limb, referral was recommended. Following preoperative ultrasonography to identify the location of remaining quill fragments, surgical exploration was performed. Approximate quill location was determined with preoperative ultrasound, but quill extraction with solely blunt dissection proved to be challenging. Intraoperative ultrasonography was then utilised to rapidly and successfully identify the remaining fragments and guided the surgeons in complete quill removal. Intraoperative ultrasound hastened the removal of fractured and embedded quills. This case highlights how intraoperative ultrasonography aided in efficiently identifying the location and orientation of embedded quills and thereby guided their surgical removal. It also highlights how imperative early medical intervention for porcupine quills is, in order to avoid disastrous complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".