On the trail of primate scent signals: A field analysis of callitrichid scent‐gland secretions by portable gas chromatography‐mass spectrometry
Bibliographic record
Abstract
Chemosignals are mediators of social interactions in mammals, providing con- and hetero-specifics with information on fixed (e.g., species, sex, group, and individual identity) and variable (e.g., social, reproductive, and health status) features of the signaler. Yet, methodological difficulties of recording and quantifying odor signals, especially in field conditions, have hampered studies of natural systems. We present the first use of the Torion® portable gas chromatography-mass spectrometry (GC-MS) instrument for in situ chemical analysis of primate scents. We collected and analyzed swab samples from the scent glands and skin from 13 groups (57 individuals) of two sympatric species of wild emperor tamarins, Saguinus imperator, and Weddell's saddleback tamarins, Leontocebus weddelli (Callitrichidae). In total, 11 compounds of interest (i.e., probably derived from the animals) could be detected in the samples, with 31 of 215 samples containing at least one compound of interest. The composition of these 31 samples varied systematically with species, group, sex, and breeding status. Moreover, we tentatively identified seven of the compounds of interest as methyl hexanoate, benzaldehyde, ethyl hexanoate, acetophenone, a branched C15 alkane, 4-methoxybenzaldehyde, and hexadecan-1-ol. As the field of primate semiochemistry continues to grow, we believe that portable GC-MS instruments have the potential to help make progress in the study of primate chemosignaling in field conditions, despite limitations that we encountered. We further provide recommendations for future use of the Torion® portable GC-MS for in situ analyses.
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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) | 0.000 | 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".