Female dispersal patterns in six groups of ursine colobus (Colobus vellerosus): infanticide avoidance is important
Bibliographic record
Abstract
Summary Under the dispersal/foraging efficiency model, colobines are predicted to be ‘indifferent mothers’, neither facilitating philopatry for their daughters nor evicting them from the natal home range because food competition is thought to be slight. We observed six groups of Colobus vellerosus at the Boabeng-Fiema Monkey Sanctuary in Ghana (2000‐2007) and recorded changes in female composition caused by observed (N = 11) and inferred (N = 12) emigrations and immigrations (N = 3). We also observed 14 immigration attempts. Most emigrating females were subadult and nulliparous. Parallel emigration was frequent. Resident females behaved aggressively to immigrating females and immigration attempts were rarely successful. Voluntary female emigration (N = 10) occurred mostly when male group membership was unstable or in association with the immigration of all-male bands. Involuntary emigrations (N = 13) associated with increased female‐female aggression occurred in the two largest groups, where parous females targeted nulliparous maturing females. Larger groups tended to lose females and female immigration was successful only in the study group with the lowest number of females. Females appear to emigrate to reduce infanticide threat although feeding competition is reduced in smaller groups as well. C. vellerosus at BFMS are better described as ‘incomplete suppressors’.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".