Urine washing and urinary odour profiles in relation to dominance rank status in wild male capuchin monkeys ( <i>Cebus imitator</i> )
Bibliographic record
Abstract
Urine plays an essential role in mammalian olfactory communication, although its potential role in primates has long been overlooked owing to focus on their visual adaptations for communication. Here, we combined behavioural and chemical data to test the role of urine in signalling male dominance in white-faced capuchins ( Cebus imitator ). We predicted that: (i) urine washing (i.e. depositing urine onto hands/feet and rubbing them onto substrates) is more frequently performed by alpha than subordinate males; and (ii) the chemical composition of alpha male urine is distinct from that of subordinates. We collected 457 h of focal behavioural follows and 153 urine samples from 24 males in five groups at Sector Santa Rosa, Área de Conservación Guanacaste, Costa Rica. We extracted urinary volatile compounds into thermal desorption tubes and analysed them by gas chromatography-mass spectrometry. We found that alphas urine wash more than subordinates, especially during the dry season when urinary odours can last longer and intergroup interactions are more frequent. Additionally, dominance rank predicted a modest fraction of overall sample chemical dissimilarity. Our results support the hypothesis that urine may be an olfactory signaling medium; future experimental research is needed to test the extent to which urinary odours may be cues versus evolved signals.
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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".