In female degus, reunions are less variable when relationships are new
Bibliographic record
Abstract
Abstract When establishing new peer relationships, animals may explore different modes of interaction, testing-out dominance roles, reciprocation of affiliation, and responses to investigation. This exploration is potentially risky, as higher variability may be counterproductive to establishing expectations and trust. There is therefore a tradeoff between exploration within a new social relationship and maintaining predictable, ‘safe’ behaviours, raising questions about how animals differ in how they engage with strangers. The Chilean degu offers an opportune case study to investigate novel social situations, as females form relationships relatively rapidly with unrelated peers. We presented degu dyads with a series of 20 min ‘reunion’ sessions and found that session-to-session variability in stranger females is, in fact, lower than in cagemates, and lower than stranger or cagemate males. Reduced variability was observed only after an initial social exposure, suggesting it was a feature of new relationships rather than novelty. There was no evidence that groups differed in predictability of behaviours within a reunion. It is known that in the wild, female degus differ from males by readily forming cooperative relationships with unrelated individuals. The data therefore raise the possibility that animals predisposed to cooperation might also show reduced behavioural variability across encounters with new individuals. This work offers new results and methods for considering strategies animals use to cope with social uncertainty.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".