Flexibility in Animal Signals Facilitates Adaptation to Rapidly Changing Environments
Bibliographic record
Abstract
Charles Darwin posited that secondary sexual characteristics result from competition to attract mates. In male songbirds, specialized vocalizations represent secondary sexual characteristics of particular importance because females prefer songs at specific frequencies, amplitudes, and duration. For birds living in human-dominated landscapes, historic selection for song characteristics that convey fitness may compete with novel selective pressures from anthropogenic noise. Here we show that black-capped chickadees (Poecile atricapillus) use shorter, higher-frequency songs when traffic noise is high, and longer, lower-frequency songs when noise abates. We suggest that chickadees balance opposing selective pressures by use low-frequency songs to preserve vocal characteristics of dominance that repel competitors and attract females, and high frequency songs to increase song transmission when their environment is noisy. The remarkable vocal flexibility exhibited by chickadees may be one reason that they thrive in urban environments, and such flexibility may also support subsequent genetic adaptation to an increasingly urbanized world.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".