Dominance and geographic information contained within black-capped chickadee (Poecile atricapillus) song
Bibliographic record
Abstract
In songbirds, male song is an acoustic signal used to attract mates and defend territories. Typically, song is an acoustically complex signal; however, the fee-bee song of the black-capped chickadee is relatively simple. Despite this relative simplicity, two previous studies (Christie et al., 2004b; Hoeschele et al., 2010) found acoustic features within the fee-bee song that contain information regarding an individual’s dominance rank; however each of these studies reported a different dominance-related acoustic cue. Specifically, the relative amplitude of the two notes differed between the songs of dominant and subordinate males from northern British Columbia, while the interval pitch ratio differed between the songs of dominant and subordinate males from eastern Ontario. In the current study, we examined six acoustic features within songs from both of the chickadee populations (northern British Columbia and eastern Ontario) examined in these previous studies and used bioacoustic analyses and discriminant function analyses to determine whether there is a consistent dominance-related acoustic cue across both, or in each of these populations. Consistent with the previous findings, the current results indicate that relative amplitude differs based on dominance status in the songs from British Columbia; however, our results failed to reach significance with songs from Ontario. These results suggest that acoustic cues that signal a male’s dominance in this species vary with geographic location. Furthermore, examining songs from these two locations and one additional location in northern British Columbia, we found that discriminant function analyses could correctly classify songs based on geographic location. Considering the broad extent of the species’ range, black-capped chickadee song is considered relatively invariant; however, our results suggest that there is geographic variation in songs, although the differences are subtle compared to geographic song variation in other species.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".