Social allies modulate corticosterone excretion and increase success in agonistic interactions in juvenile hand-raised graylag geese (<i>Anser anser</i>)
Bibliographic record
Abstract
In mammals, support by a social partner may reduce stress levels and ease access to resources. We investigated the effects of the passive presence of a nearby social ally on excreted corticosterone immunoreactive metabolites and behaviour in juvenile graylag geese (Anser anser). Two groups of hand-raised juveniles (N1 = 9, N2 = 3) were tested over 1 year by positioning humans of different familiarity (i.e., the human foster parent, a familiar human, a nonfamiliar human, no human) at a standard distance to the focal geese. Their success in agonistic interactions significantly decreased with age and with decreasing familiarity of the accompanying human. The humans present modulated the excretion of corticosterone immunoreactive metabolites, with the strongest effects recorded after fledging when corticosterone metabolites were also positively correlated with agonistic behaviour. This suggests that a human foster parent may provide similar supportive benefits as goose parents do in natural families. We discuss the benefits of social alliances with regard to the integration into the flock, access to resources, and life history.
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 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 | 0.000 |
| 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) | 0.001 | 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".