Male breeding success is predicted by call frequency in a territorial species, the agile frog (<i>Rana dalmatina</i>)
Bibliographic record
Abstract
Calling behaviour and the characteristics of the male call are important for both female mate choice and male mating success in anurans. As with most other ranid frogs, males of the agile frog ( Rana dalmatina Fitzinger in Bonaparte, 1839) emit advertisement calls during the mating period. However, since males occupy and defend territories, it is not clear whether the calls serve to defend a territory and (or) to attract a mate. We investigated the relationship between male call characteristics and male breeding success in a field study by relating individual males’ call parameters (viz. call duration, number pulses, pulse rate, and fundamental frequency) with their breeding success as indicated by the number and size of egg clutches in the territories of males. We found that the number and size (in number of eggs) of clutches in the territories of males increased with decreasing fundamental frequency of calls. We found no correlation between territory characteristics and breeding success, suggesting that the observed correlation between male call characteristics and mating success is not likely to be explained by differences in territory quality, but by female potential preference for males calling with low fundamental frequency.
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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 | 0.002 |
| 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) | 0.002 | 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".