Epidemiology: Population parameters to compare dog breeds: Differences between five dutch purebred populations
Bibliographic record
Abstract
Differences in five purebred dog populations born in 1994 in the Netherlands were evaluated using different parameters. Numerically, the Golden Retriever was the largest breed (840 litters of 234 sires) and the Kooiker Dog (101 litters of 41 sires) the smallest. The litter per sire ratio was largest in the Bernese Mountain Dog (4.59) and lowest in the Kooiker Dog (2.46). The mean relatedness and the actual mean level of inbreeding in the studied generations were 0.102 and 0.056 respectively for the Bernese Mountain Dog, 0.041 and 0.046 for the Bouvier des Flandres, 0.087 and 0.061 for the Boxer, 0.020 and 0.018 for the Golden Retriever, and 0.146 and 0.070 for the Kooiker Dog. Quantification and visualization of population parameters for purebred dogs will facilitate the comparison of breeds and the comparison of breeds in different periods or countries. It appears unlikely that the increase in inbreeding is a major determinant of the possible increase in the frequency of genetic diseases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".