Estimated genetic parameters for growth traits of German shepherd dog and Labrador retriever dog guides.
Bibliographic record
Abstract
A desirable dog guide weighs 18 to 32 kg and measures 53 to 64 cm in height at the withers as an adult. Heritabilities and genetic correlations were estimated for birth weight, 42-d weight, mature weight, and mature height for 2,334 German shepherd dogs and 2,028 Labrador retrievers raised by the Seeing Eye, Inc., Morristown, NJ, from 1979 to 1997. Data included 5,006 observations for German shepherd dogs from 113 dams and 33 sires and 4,123 observations for Labrador retrievers from 89 dams and 29 sires. A mixed effects model was considered with sex and birth year as fixed effects. Random effects were animal, maternal, and litter incorporating all pedigree information available. A derivative-free REML method was used to estimate parameters. The maternal component was higher than the additive genetic component for birth weight. Heritability of mature weight was estimated as 0.57 +/- 0.07 for German shepherd dogs and 0.44 +/- 0.07 for Labrador retrievers. Mature height heritability was estimated as 0.35 +/- 0.08 for German shepherd dogs and 0.46 +/- 0.08 for Labrador retrievers. Selection for lighter dogs at maturity is predicted to decrease the average mature height, and selection for taller dogs at maturity is predicted to increase the average mature weight. The estimated genetic parameters will aid in the development of strategies to increase the probability of breeding dogs for optimum mature size.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".