Exploring breed differences in discrimination, reversal learning, and resistance to extinction in the domestic dog (Canis familiaris)
Bibliographic record
Abstract
Learning is crucial for shaping domestic dogs' behaviour through life experiences, yet not all breeds exhibit the same learning aptitude towards a particular task. The current study's objective was to identify differences in behaviour and learning performance across and within five breed clades and elucidate the underlying factors contributing into these variations. Dogs (n = 111) from five breed clades (UK Rural, Retrievers, Asian Spitz, European Mastiff, and New World) participated in a virtual learning task with their owners. Owners completed validated questionnaires of Impulsivity and Reward Responsiveness. The learning task comprised of reinforcing an arbitrary behaviour (hand-touch) through multiple sessions of Acquisition (reinforcing the hand-touch), Discrimination (reinforcing the hand-touch on one of two hands) and Reversal Learning (reinforcing the hand-touch on the opposite hand), followed by a single session of Extinction (hand-touch not reinforced). Results showed notable differences across the studied breed clades in certain learning and behavioural components. However, the observed disparities may not be entirely attributed to inherent cognitive differences among the breed clades but rather potentially influenced by contextual factors such as the human-dog communication dynamics associated with breeds' cooperativity. Furthermore, breed clades differed in the contributing factors predicting individual learning performances, which could highlight the potential effect of breeds' historical function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".