Song overlapping and matching during low‐arousal singing and their relation to visual ornaments, parental care and breeding success in the great tit (<i>Parus major</i>)
Bibliographic record
Abstract
Abstract Eavesdropping on interactions between conspecific animals provides a low‐cost method for assessing other individuals. Asymmetries in territorial counter‐singing interactions in songbirds provide a rich source of information for eavesdroppers about differences between the singers. Yet, little is known about the relationship between interactive singing in a natural, low‐arousal context among territorial neighbours and individual traits of males. We used a microphone array to monitor natural counter‐singing interactions in great tits (Parus major) during nest building, at the onset of the breeding season. We quantified song overlapping and song matching for 30 pairs (dyads) of interacting males, singing at their nest, respectively. We then compared these behaviours to five traits for 28 males: body condition, plumage ornamentation, offspring provisioning behaviour, offspring weight and breeding site quality. We found no relationship between a male song overlapping or matching behaviour and any of the measured traits. Therefore, our results do not support the idea that short‐term asymmetries in low‐arousal long‐range singing interactions among neighbours reflect differences in these fitness‐related traits. Instead, our findings suggest that such singing asymmetries have less signal value in the absence of an immediate conflict but instead reflect short‐term motivational differences, as shown in previous investigations.
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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".