Cognition in the field: comparison of reversal learning performance in captive and wild passerines
Bibliographic record
Abstract
Animal cognitive abilities have traditionally been studied in the lab, but studying cognition in nature could provide several benefits including reduced stress and reduced impact on life-history traits. However, it is not yet clear to what extent cognitive abilities can be properly measured in the wild. Here we present the first comparison of the cognitive performance of individuals from the same population, assessed using an identical test, but in contrasting contexts: in the wild vs. in controlled captive conditions. We show that free-ranging great tits (Parus major) perform similarly to deprived, captive birds in a successive spatial reversal-learning task using automated operant devices. In both captive and natural conditions, more than half of birds that contacted the device were able to perform at least one spatial reversal. Moreover, both captive and wild birds showed an improvement of performance over successive reversals, with very similar learning curves observed in both contexts for each reversal. Our results suggest that it is possible to study cognitive abilities of wild animals directly in their natural environment in much the same way that we study captive animals. Such methods open numerous possibilities to study and understand the evolution and ecology of cognition in natural populations.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".