An experimental test of kin association in the house mouse
Bibliographic record
Abstract
Studies of genetic markers have suggested that female house mice (Mus musculus domesticus) prefer spatial association and nest sharing with close kin. Further, observations of mothers in single and communal nests suggest a potential advantage of association with kin, namely, improved reproductive success through cooperative defense of young against infanticide. In semi-natural enclosures, we tested for spatial association of female mice in small groups of sisters versus small groups of virtually unrelated females. We also examined success in producing and weaning litters by sisters versus mothers that were not close kin. Sisters exhibited greater spatial association than expected, although some groups of nonsisters showed close associations as well. All 14 sisters in the enclosures produced and weaned young in communal nests. Among 15 mothers that did not have sisters available, 4 did not produce litters, 2 shared a nest, and only 3 weaned young. Although infanticide occurred for both kinds of mothers, it was significantly more common in the single nests of nonsister mothers than for sisters. Thus, sisters were more successful at weaning young, probably owing to advantages of communal nesting. These results suggest that close female kin may associate spatially, and that there are distinct reproductive advantages due to the presence of close kin. The society of house mice is generally described as male dominated, but association of female kin may constitute the basis of social grouping in house mice.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".