Morphology and somatometric growth of long-tailed macaques (<i>Macaca fascicularis fascicularis</i>) in Singapore
Bibliographic record
Abstract
Crab-eating, or long-tailed, macaques [Macaca fascicularis (Raffles, 1821)] have been studied extensively throughout their distribution in South and South-east Asia. Despite this extensive body of research, the island population of long-tailed macaques from Singapore remains virtually undescribed. In the present study, we compare the morphometric variability and patterns of growth observed in a population sample from Singapore with a composite sample from Thailand, north of the Isthmus of Kra. The results of our analyses indicate that there are statistically significant differences between the two populations in adult size and shape. For both males and females, the Singapore population is smaller than the Thai population. Relative to body length, the Singapore macaques exhibit significantly longer tails, and, relative to cranial length, they exhibit significantly more narrow faces than the Thai macaques. Although levels of sexual dimorphism for most morphometric traits are very similar, indicating similar levels of male–male competition for females, the Singapore males exhibit a significantly larger testicular volume relative to body weight, suggestive of an alternative male reproductive strategy. In addition to adult somatometric size and shape, comparisons of growth patterns relative to age and body size reveal significant differences between the two population samples. Combined, these results suggest either that statistically significant differences in adult morphology and patterns of growth can occur in presumably reproductively cohesive subspecies, or the Singapore macaques may be taxonomically distinct.
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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 | 0.001 |
| 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".