Female fowl (Gallus gallus) do not prefer alarm-calling males
Bibliographic record
Abstract
Phenotypic traits associated with reproductive outcomes are often thought to be under sexual selection. In fowl, Gallus gallus, the rate at which males produce anti-predator alarm calls is an excellent correlate of their mating and reproductive success. However, two different models can explain this relationship. Calling, like many costly traits, may be attractive to females. Alternatively, males that have recently mated may invest in their mates by increasing alarm call production. Although previous work provides strong support for the male investment hypothesis, the two hypotheses are not mutually exclusive. In this study, we tested the mate attraction hypothesis by manipulating male alarm calling rates in three separate mate choice experiments. The first experiment was conducted in a highly controlled laboratory setting. There, we used video playback techniques to present females with simulated males that differed only in their alarm calling responses to simulated predators. In the second experiment, females were presented with two live males in a naturalistic outdoor setting. One male's vocal output was supplemented with his own pre-recorded alarm calls, and the other male's was not. In the third experiment, we combined the realistic spatial scale of an outdoor context with the stringent experimental control offered by video playback. The male stimuli used in this experiment differed in their propensity to produce four intercorrelated vocal signals that are each correlated with male mating and reproductive success. These included aerial alarm calls, ground alarm calls, food calls, and crows. Results from the three experiments consistently showed that females do not prefer alarm-calling males, suggesting that male alarm calling is not a sexually selected signal.
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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 | 0.000 | 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".