Anogenital distance as a measure of male competitive ability in Rwenzori Angolan colobus
Bibliographic record
Abstract
Anogenital distance (AGD) is positively correlated to fetal androgen exposure and developmental masculinization in mammals. Independent of overall body size, AGD shows a strong positive correlation with male fertility and in rodents, AGD is a good indicator of male competitive ability and is associated with female choice. We hypothesized that AGD will also predict male competitive ability in non-human primates. To test this, we measured AGD noninvasively with a parallel laser in a wild population of Angolan colobus monkeys (Colobus angolensis ruwenzorii) in Uganda and correlated to it to their social structure. C. angolensis ruwenzorii form a multilevel society with both one-male/multifemale units (OMUs) and multimale/multifemale units (MMUs). We compared AGD in males from five OMUs and six MMUs and related it to their fecal androgen metabolite concentrations, dominance rank and body size, and to the number of females in their unit. Males in OMUs had greater access to females, so were predicted to have longer AGDs, but this was not found. AGD also did not correlate overall with mean fecal androgen metabolites in MMUs. However, AGD was correlated with dominance rank in MMUs, demonstrating that higher-ranking males in these multimale units had longer AGDs. Body size did not show the same relationship with dominance rank, suggesting that male rank was not just a reflection of absolute male size. Our findings indicate that AGD predicts male competitive ability in this species and that it may be a useful correlate throughout the non-human primates. These results also support the idea that prenatal androgen exposure increases the likelihood of the expression of behaviors that maintain high dominance rank.
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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".