Aggressive signalling strategies in black-capped chickadee territorial vocal interactions/Stratégies aggressive de signalisation dans les interactions vocales du territoire en mésange à tête noire.
Bibliographic record
Abstract
The traditional view of birdsong indicates that it functions in territory defence and mate attraction. Recent literature focuses on aggressive signalling between males during territorial song contests. Using a protocol that simulates territorial intruders with song playback and a taxidermic model, four previous studies showed that quiet song predicts attack in several species. Using this protocol, I examined aggressive signals in black-capped chickadees, Poecile atricapillus . I explored which signals predict attack on a taxidermic mount, a potential graded signalling system, and how individual rank affects aggressive signalling. I found song rate and gargle calling predict attack in chickadees. Also, song rate and gargle calling may constitute a graded signalling system used to communicate increasing levels of threat. Finally, I found no effect of male rank on aggressive signalling strategies. This thesis provides new insight into avian aggressive signalling and new avenues for research on graded signalling.
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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".