Individual variation in the dear enemy phenomenon via territorial vocalizations in red squirrels
Bibliographic record
Abstract
Abstract Territoriality arises when the benefits of resources exceed the costs of defending them. The dear enemy phenomenon, where familiar territorial neighbours refrain from intruding on one another and mutually reduce their defensive efforts, allows for reduction of these costs but requires discrimination between conspecifics. We hypothesized that territorial vocalizations in red squirrels ( Tamiasciurus hudsonicus ) are used for this discrimination. We performed a speaker replacement experiment where red squirrels ( ) were temporarily removed from their territories and replaced with a speaker broadcasting their own call, an unfamiliar call, or silence. Contrary to our prediction, there were no differences in overall intrusion risk among our three playbacks, but the identity of intruders did vary. Existing variation in familiarity within territorial neighbourhoods should be considered, rather than the binary classification of familiar or stranger, when studying dear enemy effects. We also discuss the variable importance of silence in acoustic territorial populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".