A ventral diaphragmatic advancement technique to repair a large congenital peritoneopericardial diaphragmatic hernia in a dog
Bibliographic record
Abstract
OBJECTIVE: To report a ventral diaphragmatic advancement technique to repair a large congenital peritoneopericardial diaphragmatic hernia in a dog. ANIMAL: A 5-month-old 15-kg entire male Labrador Retriever. CLINICAL PRESENTATION, PROGRESSION, AND PROCEDURES: The dog presented with a history of diarrhea for a week and acute-onset lethargy and vomiting for 3 days. Clinical examination revealed borborygmi on auscultation of the chest, and subsequent imaging showed a congenital peritoneopericardial diaphragmatic hernia. TREATMENT AND OUTCOME: The ventro-central diaphragmatic defect was repaired with a pericardial flap, which subsequently failed 7 months later. The revision surgery was performed with a novel surgical technique. The defect was closed by means of incising the ventral attachments of the diaphragm either side of the defect and sliding it medially to allow a tension-free closure. The ventral aspect of the incised diaphragm was reattached with circumcostal sutures and the central defect closed. The dog recovered rapidly and without complication. An excellent outcome was reported after surgery. CLINICAL RELEVANCE: This novel technique was a simple method to repair a peritoneopericardial diaphragmatic hernia and had good clinical results in this case.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".