Reward Type Affects Dogs' Performance in the Cylinder Task
Bibliographic record
Abstract
The cylinder task, which requires detouring around an obstacle to retrieve a reward, is a popular method for assessing inhibitory control in dogs and other species. However, performance on the cylinder task has poor construct validity represented by its lack of correlations with other inhibitory control measures, ceiling effects, and influence of non-cognitive factors. In the current study we examined whether reward type affected dogs’ performance in the cylinder task. We compared working-line Labrador retrievers' (n = 38) performance on two conditions of the cylinder task, one with a treat and another with a ball reward, and found that dogs performed significantly better when a treat was used. Our secondary goal was to determine if how we defined a dog’s response changed interpretation of the results. We found better performance when a narrower definition of an inhibitory control failure was used. Further, under one condition of reward type and response definition, cylinder task performance was predicted by another measure of inhibitory control (Dog Impulsivity Assessment Scale scores). These findings are the first to show the effect of reward type on cylinder task performance as well as a relationship between the cylinder task and another measure of inhibitory control in dogs. We discuss these results in relation to previous findings on the effects of task features on cylinder task performance and its construct validity.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".