What factors really influence domestic dogs’ (Canis familiaris) search for an item dropped down a diagonal tube? The tubes task revisited.
Bibliographic record
Abstract
It has been suggested that domestic dogs-like young human children-have a "gravity bias"; they expect an unsupported object to fall straight down, regardless of any obstacles that redirect or halt its path. In the diagonal tube task, this bias is revealed by a persistent tendency to search the incorrect location directly beneath the top of the tube the item is dropped into, rather than the correct location attached to the bottom of the tube. We presented dogs (N = 112) with seven different versions of the diagonal tube task, to examine what factors influence their search behavior for an object dropped down a diagonal tube, and investigate their physical reasoning skills more generally. Contrary to previous claims, we found no evidence for dogs exhibiting a persistent, or even a Trial 1, gravity bias. However, dogs were also unable to search correctly for the reward, even when it could be heard rolling through the tube, though they succeeded when the tube was transparent (Experiments 1a-c). Experiment 2 suggested that dogs might search on the basis of proximity, but Experiments 3a-b ruled this out and showed that they prefer to commence searching at the center of the apparatus. Finally, when potential sources of bias were eliminated from the task (Experiment 4), dogs' performance was improved, but still not above chance, suggesting that they are unable to reason about the tube's physical-causal mechanism. We conclude that, on current evidence, the gravity bias might be unique to some primate species. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".