Analysis of genetic and environment factors affecting the training acceptance of puppies
Bibliographic record
Abstract
Based on testing records between 2000 and 2007 of 1992 puppies (6-month-old) maintained at a dog breeding center in Nanjing,the effect of genetic and environment factors affecting the training acceptance rate of puppies was analyzed by means of the general linear model (GLM).The results indicated:the breed,the age of dam,the season of birth and parents significantly affected the acceptance rate (P 0.05) ;the sex,the litter size at 2-months of age and the rearing and training mode had little effect on the acceptance rate (P 0.05) ;the acceptance rates of Labrador retriever and English Springer Spaniel were significantly higher than that of German Shepherd Dog (P 0.05),and the puppies born in autumn or before 1.5 years old of dams had high ejection rate (P 0.05).The heritability of the acceptance rate,fetch and fearfulness of puppies of German Shepherd Dog and Labrador retriever were medium or high,and English Springer Spaniel were lower.
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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".