SOURCE LEVEL OF MALE VOCALISATIONS IN THE GENUS <i>MIROUNGA</i> : REPEATABILITY AND CORRELATES
Bibliographic record
Abstract
Male vocalisations have an important role in mating tactics, breeding strategies and sexual selection. Most studies of vocalisations are concentrated on the time and frequency domains, while the intensity of sound, an important acoustic parameter that should be related to body size, is almost completely ignored as a possible honest signal of resource holding potential (RHP) and cue for mate choice. In this paper, we analyse the repeatability, the correlations with age and size, and the relationship with breeding status of source level (SL) of male vocalisations in the two species of elephant seals (Mirounga leonina and M. angustirostris). We found a high repeatability of SL, equal or higher than the repeatability of frequency domain parameters estimated in a previous study. Southern elephant seal males were significantly larger and produce significantly more powerful vocalisations than northern males. Moreover, in each species SL was related to age, body size, and breeding status of males, but relationships were weak and accounted for just a small proportion of SL variance. We conclude that, although SL may be an honest signal of gross differences of RHP, it is not, by itself, a good candidate for the transmission of high-resolution information on individual phenotype. A combination of SL and frequency components could be, on the contrary, an effective way to communicate RHP.
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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 | 0.001 | 0.002 |
| 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".