Male juvenile golden snub-nosed monkeys acting as the mountee to receive grooming in their same-sex mounts
Bibliographic record
Abstract
Abstract Same-sex mounts provide male juvenile golden snub-nosed monkeys (Rhinopithecus roxellana) with opportunities to practice heterosexual copulatory skills and are often followed by grooming (post-mounting grooming, PMG). We hypothesized that juveniles acted as the mountee and provided mounting opportunities to receive grooming from their peer mounter. Here, we observed same-sex mounts among male juveniles (N = 5) in a captive group of R. roxellana in Shanghai Wild Animal Park, China, from November 2014 to June 2015. Among 1,044 mounts recorded, 45.40% were accompanied by PMG initiated by the mounter and only 3.74% were followed by PMG initiated by the mountee. Mountees were more likely to receive PMG when they performed a mounting solicitation than when they did not, or when they were mounted for a longer time (even if they did not solicit). Over a long timeframe (1 month), mountee’s tended to choose partners who groomed them more often than others after mounting, regardless of how long the grooming lasted. However, whether the mounter groomed the mountee did not predict the mounting direction in their subsequent mount. Our results suggest that, in the context of same-sex mounts, juveniles provide mounting opportunities to receive grooming from peers on a long-term, rather than on a short-term basis. This study provides the first evidence that juveniles’ same-sex mounting strategy may be associated with the grooming market in nonhuman primates, which necessitates further investigation with large free-ranging groups due to the limited sample size of individuals and the captive setting of the current study.
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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 | 0.001 | 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) | 0.002 | 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".