Mating Tactics in Male Grey‐Cheeked Mangabeys (<i>Lophocebus albigena</i>)
Bibliographic record
Abstract
Abstract Reproductive tactics of males can change with individual quality, relatedness and social structure. Here we describe the behaviours of male grey‐cheeked mangabeys towards other males, and females and their offspring (Lophocebus albigena) in relation to male status (high‐ranking/low‐ranking/transient) and group composition in Kibale National Park, Uganda. High‐ranking males had the highest mating success, frequency of loud calls, mate guarding and aggression towards females and males. Only transient males were often observed to be aggressive towards juveniles, while some high‐ranking males provided infant care. Mating tactics of high‐ranking males varied greatly among the five studied groups, probably as a function of the intensity of male–male competition. These results are discussed with regard to the role of male–male competition and behaviours that could affect female mate choice as tactics to obtain reproductive success.
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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 | 0.000 | 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".