Repertoire composition and singing behaviour in two eastern populations of the Hermit Thrush (<i>Catharus guttatus</i>)
Bibliographic record
Abstract
Although it is highly recognisable, relatively little is known about the repertoire composition and singing behaviour of the Hermit Thrush (Catharus guttatus). To address this, we recorded spontaneously singing males in two eastern populations (Halifax, NS (n = 11) and Hancock County, ME (n = 7)) and analysed the recordings with respect to repertoire size, basic song type characteristics and song syntax. Males had song type repertoires of 7–12 song types, and no song type sharing between individuals was observed within or between populations. While frequency-related structural characteristics of the song types were the same between the populations, song type duration (especially that of the introductory note) differed significantly. The song types within each repertoire could be categorised into high and low song types based on introductory note frequency, and these song type categories also differed with respect to the amount and distribution of spectral energy. In both populations, males sang with immediate variety, never repeating the same song type consecutively, and preferentially used some song-type to song-type transitions more than others. In addition, we found correlational evidence of changes in singing behaviour (e.g., the relative use of low versus high song types) over the course of the breeding season. We discuss these findings in the context of other songbird research as well as their implications for future work examining how Hermit Thrush males utilise their songs in defending territories and attracting mates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".