Evidence for multicontest eavesdropping in chickadees
Bibliographic record
Abstract
Animals eavesdrop on dyadic interactions between other individuals to gather information for future mate choice and territory defense decisions. The capacity for eavesdroppers to combine information gathered from overhearing multiple two-way interactions is poorly studied. We tested whether inexperienced (second year) and older (after second year) male black-capped chickadees (Poecile atricapillus) eavesdrop on rivals' song contests to evaluate the relative threat levels of multiple unfamiliar territorial intruders. We used a multiple speaker playback experiment to simulate 3 male territorial intruders (A, B, and C) engaging in 2 successive dyadic song contests, presenting focal males with the information that A was more threatening than B, and B was more threatening than C. We then assayed the response of focal males when presented with simulated intruders A and C without relative information. We predicted that males would defend against the intruder perceived to be the greater threat. Focal males initially responded toward the more threatening intruder (A) significantly more than the less threatening intruder (C), consistent with our predictions. Older birds approached the more threatening intruder (A) significantly more than the less threatening intruder (C), whereas young males showed more variable responses. Our results suggest that male chickadees were able to acquire relative threat information from separate song contests that influenced their responses toward rivals paired in novel contests. These findings indicate that territorial songbirds in communication networks may be capable of integrating information gathered through eavesdropping on multiple interactions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".