Natural variation in developmental condition has limited effect on spatial cognition in a wild food-caching bird
Bibliographic record
Abstract
Laboratory studies show that increased physiological burden during development results in cognitive impairment. In the wild, animals experience a wide range of developmental conditions, and it is critical to understand how variation in such conditions affects cognitive abilities later in life, especially in species that strongly depend on such abilities for survival. We tested whether variation in developmental condition is associated with differences in spatial cognitive abilities in wild food-caching mountain chickadees. Using tail feathers grown during development in juvenile birds, we measured feather corticosterone (Cort f ) levels and growth rates and tested these birds during their first winter on two spatial learning tasks. In only 1 of the 3 years, higher feather Cort f was negatively associated with memory acquisition. No significant associations between feather Cort f and any other measurement of spatial cognition were detected in the other 2 years of the study or between feather growth rate and any measurement of cognition during the entire study. Our results suggest that in the wild, naturally existing variation in developmental condition has only a limited effect on spatial cognitive abilities, at least in a food-caching species. This suggests that there may be compensatory mechanisms to buffer specialized cognitive abilities against developmental perturbations.
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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 | 0.000 | 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".