Song overlapping in territorial defense and other contexts by the Hermit Thrush ( <i>Catharus guttatus</i> )
Bibliographic record
Abstract
Songbirds, which rely heavily upon acoustic communication, employ a variety of strategies to reduce the degree to which their songs are masked by other sounds within the environment. One such strategy is to make active adjustments to song timing to avoid temporally overlapping other environmental sounds. While playback studies in many different songbird species have demonstrated that territorial males avoid overlapping conspecific songs in that context, there is comparatively little known about how such behavior varies across contexts. For example, there is relatively little information on avoidance of overlapping in naturalistic interactions (e.g., countersinging) among conspecific singers; likewise, few studies have assessed the degree to which males avoid overlapping heterospecific songs. Songbird researchers have also explored possible communicative functions of song overlapping, most notably the idea that overlapping conveys information related to aggression. The objectives of the present study were to compare song overlapping across contexts and to assess the relationship between song overlapping and physical responses to conspecific playback in the Hermit Thrush (Catharus guttatus). Degree of song overlapping in response to conspecific (n = 29) and heterospecific playback (n = 31), as well as during naturally occurring countersinging (n = 21 pairs), was compared to chance levels. Avoidance of overlapping occurred in all 3 contexts, although to a lesser degree in response to heterospecific playback. Comparison of physical responses to song overlapping during conspecific playback revealed no association, aligning with recent studies in other species indicating that song overlapping is not an aggressive signal. Instead, the avoidance of song overlapping appears to be an important tool for decreasing the risk of acoustic interference posed by both conspecific and heterospecific songs.
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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".