CT morphology of anomalous systemic arterial supply to normal lung in dogs
Bibliographic record
Abstract
Anomalous systemic arterial supply to the normal lung (ASANL) is a rare congenital anomaly in humans, in which the systemic arteries supply the basal segments of the lower lobe. It has a normal bronchial connection, but lacks a normal pulmonary artery. This anomaly has not been previously reported in the veterinary literature. The objectives of this retrospective descriptive study were to characterize the CT findings and clinical features of ASANL , and to determine the breed predisposition in a population of referral canine cases. Thoracic CT images, in which the caudal lung lobes were fully inflated and the pulmonary artery could be traced to the periphery, were reviewed. A total of 1,950 dogs were enrolled, and the aberrant vasculature equivalent to ASANL in humans was detected in 48 dogs. Shetland Sheepdogs (7/48, odds ratio [OR] = 8.0, P < 0.00001), Miniature Dachshunds (19/48, OR = 3.9, P < 0.00001), and Labrador Retrievers (6/48, OR = 4.5, P = 0.0009) were over-represented. The affected lung lobes were the right caudal lobe (24/48, 50%), the left caudal lobe (21/48, 43.8%), and bilateral caudal lobes (3/48, 6.3%). The aberrant vessels originated from the left gastric artery (14/48), descending thoracic aorta (8/48), celiac artery (6/48), and splenic artery (1/48). In the remaining 19 cases, the origin of the aberrant vessels could not be determined. Although the clinical significance of ASANL in dogs remains unclear, surgeons should be aware of this finding prior to lobectomy of the caudal lung lobes to avoid intraoperative systemic arterial bleeding.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".