Acoustic cues to individual identity in the rattle calls of common blackbirds: a potential for individual recognition through multi-syllabic vocalisations emitted in both territorial and alarm contexts
Why this work is in the frame
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Bibliographic record
Abstract
Vocal signals convey many types of information, and individually recognizable cues can benefit signallers and receivers, as shown in birdsongs that are used in the contexts of mating and territoriality. Bird calls are typically less complex than songs and thus are likely to convey less information. However, the rattle calls of some species serve a dual function, being emitted as an anti-predator and deterrence signal, and thus may encode information on individual identity. We investigated these questions in the common blackbird ( Turdus merula ), which emits complex rattle calls in both territorial and alarm contexts. The vocalisations of free-living males were elicited and recorded by playing back songs of unknown males in birds’ territories (territorial context) and also while approaching individuals (predator context). These song-like highly-structured multi-syllabic calls typically had three types of elements. Acoustic and statistical analyses revealed, through elevated repeatability indexes, that most of the acoustic measurements used to describe the complexity of the calls (structural, temporal and frequency parameters) were highly variable, due to inter-individual differences. The size of the call and the characteristics of the starting element only were able to discriminate a high portion of the individual calls. Beyond the very well studied songs of oscines, calls therefore deserve more attention as they also carry a potential for conveying information on individual identity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it