Similar recent selection criteria associated with different behavioural effects in two dog breeds
Bibliographic record
Abstract
Selection during the last decades has split some established dog breeds into morphologically and behaviourally divergent types. These breed splits are interesting models for behaviour genetics since selection has often been for few and well‐defined behavioural traits. The aim of this study was to explore behavioural differences between selection lines in golden and Labrador retriever, in both of which a split between a common type (pet and conformation) and a field type (hunting) has occurred. We hypothesized that the behavioural profiles of the types would be similar in both breeds. Pedigree data and results from a standardized behavioural test from 902 goldens (698 common and 204 field) and 1672 Labradors (1023 and 649) were analysed. Principal component analysis revealed six behavioural components: curiosity, play interest, chase proneness, social curiosity, social greeting and threat display. Breed and type affected all components, but interestingly there was an interaction between breed and type for most components. For example, in Labradors the common type had higher curiosity than the field type ( F 1,1668 = 18.359; P < 0.001), while the opposite was found in goldens ( F 1,897 = 65.201; P < 0.001). Heritability estimates showed considerable genetic contributions to the behavioural variations in both breeds, but different heritabilities between the types within breeds was also found, suggesting different selection pressures. In conclusion, in spite of similar genetic origin and similar recent selection criteria, types behave differently in the breeds. This suggests that the genetic architecture related to behaviour differs between the breeds.
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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 | 0.001 |
| 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 | 0.001 |
| 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".