Characterising the flight song: repeatable individual variation of Ovenbird song features
Bibliographic record
Abstract
The songs of most passerines have been well described; however, songs from some species are more difficult to record and have yet to be characterised. The Ovenbird (Seiurus aurocapilla) flight song occurs rarely, is complex in its syllable composition, and its function is still not well understood. We examine the structure of the Ovenbird flight song using the largest sample of warbler flight songs to date (n = 396, 23 individuals) from autonomous recordings made in Sault Ste. Marie, Canada. We characterised the syllable repertoire of this song, examined song syntax, compared syllable sharing among males, and estimated repeatability of several song features. Syllable repertoires varied among males and they appeared to transition differently between syllables while singing, but we found no evidence for syllable sharing between neighbours. Male Ovenbirds were significantly repeatable in the syllable compositions of their flight songs, but repeatability estimates were lower for terminal compared to introductory segments. We find weak evidence of a negative relationship between song features at the within-individual level, suggesting that individuals also demonstrate considerable plasticity when singing. Understanding variation in the Ovenbird flight song will lead to a better understanding of the function(s) of this song type.
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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 | 0.001 | 0.001 |
| 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".