Are the alarm calls of North American red squirrels (Tamiasciurus hudsonicus) functionally referential?
Bibliographic record
Abstract
Abstract North American red squirrels are a small-bodied and solitary-living species that faces a diversity of predators and produces two different variants of alarm calls in response to them. Recent studies have yielded conflicting interpretations of the predator-specific and functionally referential nature of these alarm call variants. We undertook a systematic set of playback experiments to quantify the responses of red squirrels to alarm calls produced by other squirrels during encounters with different predators. The experiment was designed to test a core requirement of functionally referential alarm calls, namely that different alarm call types induce distinct and functionally appropriate escape responses in listeners. Results indicated that squirrels registered and responded to alarm calls produced by others; however, their responses were not differentiated according to the type of alarm call they heard and, thus, did not provide evidence that the different alarm call variants hold any predator-specific, referential value. These outcomes are discussed in light of complementary work on alarm call production in red squirrels and broader aspects of this species' life history in an effort to better understand the necessary and sufficient pressures promoting the evolution of referential call systems in animals.
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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".