Primary Infundibular Stenosis and Pedigree Analysis in Three Golden Retriever Littermates
Bibliographic record
Abstract
Three eight-week-old Golden Retriever puppy littermates were evaluated because of left basilar systolic murmurs and were diagnosed with primary infundibular stenosis. Pedigree analysis in this line was also performed to identify a mode of inheritance. All dogs were asymptomatic at the time of diagnosis; two of the three had congenital lesions in addition to primary infundibular stenosis. Two additional affected dogs were identified in the line, and pedigree analysis suggested an autosomal recessive mode of inheritance. Another, unrelated golden retriever was also identified with isolated infundibular stenosis in the record database. Primary infundibular stenosis should be considered in the differential diagnoses for golden retriever dogs with a left basilar systolic murmur, and is often associated with complex congenital cardiac disease. Primary infundibular stenosis may worsen in severity with time, and in this line of dogs an autosomal recessive pattern of inheritance is likely.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".