Data from: Benefits of living closer to kin vary by genealogical relationship in a territorial mammal
Bibliographic record
Abstract
While cooperative interactions among kin are a key building block in the societies of group-living species, their importance for species with more variable social environments is unclear. North American red squirrels (Tamiasciurus hudsonicus) defend individual territories in dynamic neighbourhoods and are known to benefit from living among familiar conspecifics, but not relatives. However, kin-directed behaviours may be restricted to specific genealogical relationships or strongly mediated by geographic distance, masking their influence at broader scales. Using distance between territories as a proxy for the ability of individuals to interact, we estimated the influence of primary kin (parents, offspring, siblings) on the annual survival and reproductive success of red squirrels. This approach revealed associations between fitness and access to kin, but only for certain genealogical relationships and fitness components. For example, females had enhanced annual survival when living closer to their daughters, though the reverse was not true. Most surprising was the finding that males had higher annual reproductive success when living closer to their father, suggesting possible recognition and cooperation among fathers and sons. Together, these findings point to unexpected nuance in the fitness consequences of kinship dynamics for a species that is territorial and largely solitary.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.022 |
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".