Female preference for a male sexual trait uncorrelated with male body size in the Palmate newt (Triturus helveticus)
Bibliographic record
Abstract
Abstract Mate choice is often based on the assessment of multiple traits. Depending on whether traits provide redundant or different information about male characteristics, correlation between traits is expected to arise or not. In species where size increases with age, body size can be a reliable indicator of adult survival whereas secondary sexual traits advertise other qualities like the ability to exploit local resources. However, because of correlations between morphological traits it is often difficult to determine whether females base their preference on the absolute or the relative size of secondary sexual traits. We addressed this issue in the palmate newt, Triturus helveticus. We selected the two most variable traits, body size and filament length, whose weak correlation suggested that they could signal different aspects of male condition or quality. We tested female preference for both traits in two experiments in which we controlled either for body size or filament length. Females preferred males with long filament in experiment 1 and males with small body sizes in experiment 2. The preference for an exaggerated trait like the caudal filament is not unexpected in a context of inter-sexual selection. In contrast, the preference for small males contrasts with usual findings on mate choice. However, body size might not be a reliable quality indicator because males of different cohorts can experience different conditions throughout their life. The caudal filament, grown each breeding period, likely reflects male condition. By assessing such a character, females might evaluate the performance of a potential partner in the current environment regardless of its age.
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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) | 0.002 | 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".