Avian communication networks: how audible are mountain chickadee males during dawn signalling?
Bibliographic record
Abstract
My thesis investigates how urban noise influences the relative audibility of songs to female Mountain Chickadees (Poecile gambeli), who assess male signalling at dawn while roosting within the nest cavity. Over two breeding seasons, I monitored Mountain Chickadees breeding on an urban/rural interface in Kamloops, BC, Canada. I broadcast typical Mountain Chickadee songs, with or without added noise, towards recently unoccupied nests while simultaneously re-recording these songs with microphones outside and inside the nest box to determine the relative audibility in relation to both distance and presence/absence of noise. I then tracked individual males’ behaviour and movement during dawn signalling, while passively recording their songs with microphones — outside and inside the nest box — to determine the relative audibility of signals from the perspective of the roosting female. The relative audibility of songs decreased with increasing distance from the nest, which was compounded by increased urban noise. During dawn signalling, urban males respond to these effects by remaining closer to the nest, resulting in their songs being more audible within the nest than their rural counterparts. Overall, ambient noise and distance had an interactive effect on relative audibility of songs, suggesting complex dynamics of communication networks that may result in a trade-off, where males are forced to prioritize directing their signals to either their social mates or neighbours.
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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 | 0.001 | 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".