Social behavior in dog puppies: Breed differences and the effect of rearing conditions
Bibliographic record
Abstract
INTRODUCTION: Most of the studies investigating the effect of early rearing environment in dogs used laboratory dogs and reported that early experiences markedly affect the puppies' behavior. However, the subjects of these experiments cannot be considered as representatives of family dogs. METHODS: In this study, we investigated whether different raising conditions shape social behavior toward humans in 8-week-old family dog puppies of two breeds, Labrador and Czechoslovakian wolf dog. The puppies were tested in a series of tests that represented typical situations of family dogs. RESULTS: We found that Czechoslovakian wolf dog puppies were more active than Labrador puppies in general, as they were more likely to explore the environment and the objects and spent more time doing so. Tendency to gaze at humans also varied between breeds, but in a context-specific way. Additionally, puppies housed separately from their mother interacted more with toys, puppies housed in a kennel tended to stay closer to the experimenter than puppies raised in the house, and puppies housed in a kennel tended to stay in the proximity of the experimenter more than puppies raised in the house. CONCLUSIONS: Our results provide evidence for early keeping conditions influencing social behavior and also highlight breed differences in puppies' behavior. Whether these differences are due to different developmental patterns and/or behavioral predispositions remains to be explored.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".