Personality is correlated with natal dispersal in North American red squirrels (Tamiasciurus hudsonicus)
Bibliographic record
Abstract
Individual natal dispersal behaviour is often difficult to predict as it can be influenced by multiple extrinsic and intrinsic factors. Individual differences in personality have been shown to be an important correlate of dispersal behaviour. However, the relationships between personality traits and dispersal are often inconsistent within and across studies and the causes of these discrepancies are often unknown. Here we sought to determine how individual differences in activity and aggression, as measured in an open-field trial, were related to natal dispersal distance in a wild population of North American red squirrels ( Tamiasciurus hudsonicus ). For 14 cohorts, while individual aggression consistently had no association with dispersal distance, the association between activity and dispersal fluctuated through time, mediated by population density. The environmental-dependence of the relationship between personality and dispersal in this population is indicative of the importance of considering external conditions when predicting dispersal behaviour.
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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 | 0.000 | 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".