Large Segmental Mandibulectomy for Treatment of an Undifferentiated Sarcoma in a Horse
Bibliographic record
Abstract
OBJECTIVE: To describe a large segmental (sub-total) mandibulectomy for removal of an undifferentiated sarcoma in a horse. STUDY DESIGN: Clinical report. ANIMALS: A 10-year-old mare. METHODS: A combination of methods including computed tomography (CT) were used to diagnose a large undifferentiated sarcoma of the right mandible. A large segmental mandibulectomy extending from 3 cm below the right temporomandibular joint to immediately caudal to tooth 407 was used to perform an en-bloc resection of the mass under general anesthesia. RESULTS: Surgery time was 11 hours and 35 minutes and total anesthesia time, 12 hours and 40 minutes. The mare was eating well 3 days after surgery. Some postoperative skin sloughing occurred, but the cosmetic and functional outcome was good. The mare continued to do well, with no evidence of disease recurrence, 24 months after surgery. CONCLUSIONS: Three-dimensional reconstruction of the CT images was instrumental in surgical planning. A very large portion of the mandible can be removed in a horse with acceptable cosmetic and functional outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".