Not only big bulls — Correlation between morphometry, reproductive success, and testosterone level in a flooded savannah population of the Spectacled Caiman (<i>Caiman crocodilus</i>)
Bibliographic record
Abstract
Testosterone is a steroid hormone involved in the expression of many morphological, physiological, and behavioral traits that arguably affect reproductive success. The evidence for that link is, however, incomplete or absent in the research on crocodilian species. Testosterone levels are also known to change throughout the breeding season, often on an hourly basis, which may further complicate studying their relationship with breeding success. We tested here whether baseline testosterone levels, measured out of the breeding season, are correlated with morphometry and reproductive success in Spectacled Caiman (Caiman crocodilus (Linnaeus, 1758)). Paternity tests, based on the amplification and genotyping of eight fluorochrome labeled microsatellites, failed to support a continuous relationship between these variables. Although adult males of all sizes contribute to reproduction, paternity was overrepresented in a few males with high values of maleness index (bigger males), supporting a despotic or pyramidal hierarchy among males. Maternity assignments supported the existence of multiple paternity, a phenomenon previously attributed in this species to the lack of large males caused by human hunting. The idea of larger males having more offspring is widespread in crocodilians, but to our knowledge, this is the first investigation that prove this dogma.
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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 | 0.001 | 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) | 0.002 | 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".