The successful surgical removal of a massive maxillary palatine osteoma in a dog
Bibliographic record
Abstract
Abstract A 1.5‐year‐old, spayed, female labrador x kelpie presented with a massive solitary palatine osteoma. En bloc excision required excision of palatine, maxillary and ventral vomer bone. The subsequent defect was closed with a combination of a left angularis oris buccal mucosal interpolation flap, right buccal mucosal rotational flap and rostral advancement of the remaining soft palate. The procedure was tolerated by the patient, with no major complications from the surgery. Histopathological examination of the excised tissue indicated complete excision of the osteoma. At the time of the publication, no recurrence had occurred, and the owners considered the procedure to provide excellent post‐operative results. The use of these soft tissue techniques allowed complete excision of the neoplasia from this difficult anatomic location in a single procedure without the need for revision surgery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".