Learning to cope: vocal adjustment to urban noise is correlated with prior experience in black-capped chickadees
Bibliographic record
Abstract
Urban noise can interfere with avian communication through masking, but birds can reduce this interference by altering their vocalizations. Although several experimental studies indicate that birds can rapidly change their vocalizations in response to sudden increases in ambient noise, none have investigated whether this is a learned response that depends on previous exposure. Black-capped chickadees (Poecile atricapillus) change the frequency of their songs in response to both fluctuating traffic noise and experimental noise. We investigated whether these responses to fluctuating noise depend on familiarity with noise. We confirmed that males in noisy areas sang higher-frequency songs than those in quiet areas, but found that only males in already-noisy territories shifted songs upwards in immediate response to experimental noise. Unexpectedly, males in more quiet territories shifted songs downwards in response to experimental noise. These results suggest that chickadees may require prior experience with fluctuating noise to adjust vocalizations in such a way as to minimize masking. Thus, learning to cope may be an important part of adjusting to acoustic life in the city.
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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 | 0.000 |
| 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".