Surgical repair of a severely comminuted maxillary fracture in a dog with a titanium locking plate system
Bibliographic record
Abstract
A four-year old male Labrador Retriever was admitted with head trauma after being hit by a car. The dog had sustained multiple nasal, maxillary, and frontal bone fractures that resulted in separation of the maxilla from the base of the skull. A severely comminuted left zygomatic arch fracture was also present. These fractures were all repaired using a point contact, locking titanium plate system, in a single procedure that resulted in excellent postoperative occlusion and immediate function. Healing was uneventful. Full function and excellent cosmetic appearance were evident 13 months after surgery. This case illustrates the ease of repair and the success of treatment of severely comminuted maxillofacial fractures by conforming to basic biomechanical principles taken directly from the human experience and successfully applied to the dog; these included multiple plate application along the buttresses and trusses of the facial skeleton. The plate fixation was applied to bridge the multiple fractures along the most appropriate lines of stress. The small size of the plates, and the ability to easily contour them to adapt to the bone surface in three-dimensions, allowed their placement in the most appropriate positions to achieve sufficient rigidity and lead to uncomplicated healing without any postoperative 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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".