Lateralization of the diaphragm for thoracic wall reconstruction in a dog
Bibliographic record
Abstract
CASE DESCRIPTION: A 7-year-old 35-kg (77-lb) neutered male Labrador Retriever was evaluated because of a 1-month history of a rapidly growing mass associated with the right caudal aspect of the thoracic wall. CLINICAL FINDINGS: CT examination revealed an aggressive, osteolytic mass lesion centered around the ventral aspect of the right ninth rib with osteolysis of that rib and focal invasion into the right external abdominal oblique muscle. Preoperative cytologic and histologic findings were most consistent with a chondrosarcoma. TREATMENT AND OUTCOME: The mass and the eighth, ninth, and tenth ribs were resected, and thoracic wall reconstruction was performed with a novel surgical technique involving lateralization of the diaphragm. The dog recovered rapidly and without complications other than a small seroma; no paradoxical chest movement developed, and the cosmetic outcome was good. An excellent quality of life was reported after surgery until the dog was euthanized because of underlying disease progression 6 months later. CLINICAL RELEVANCE: Diaphragmatic lateralization was a simple method of caudal thoracic wall reconstruction that had good clinical results in this case. Research is needed to further assess the safety, reliability, and potential complications of this procedure in dogs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".