Eavesdropping and communication networks revealed through playback and an acoustic location system
Bibliographic record
Abstract
Our understanding of animal communication is expanding from a dyadic framework of one signaler and one receiver to a broader communication network model, yet empirical studies of communication networks are scarce. To investigate whether territorial males eavesdrop on interactions occurring outside of their territory boundaries and to quantify the neighborhood-level effects of song contests, we simulated diurnal dyadic countersinging exchanges in the undefended spaces between established territories of black-capped chickadees (Poecile atricapillus). In each of 10 neighborhoods, we used stereo playback to simulate interactions between 2 unknown rivals. We simulated 2 types of song contests that differed only in the relative timing and patterning of the songs of the contestants; aggressive treatments contained frequency matching and song overlapping, whereas submissive treatments contained neither matching nor overlapping. We used a 16-microphone acoustic location system to record males in the neighborhood surrounding the playback apparatus. Territorial chickadees responded more intensely to the aggressive treatments than the submissive treatments. Neighborhood song output (number of songs produced by all individuals in the recording area) was twice as high after aggressive playback than after submissive playback. Males with territories bordering the playback apparatus had higher song output than males who were more than one territory removed from the playback apparatus. We did not find an influence of male dominance rank on playback responses. Our results reveal that territorial male chickadees eavesdrop on and respond to interactions occurring outside of their territory boundaries.
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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 | 0.000 | 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".