Effects of anthropogenic noise and light on the vocal and spatial behaviour of birds
Bibliographic record
Abstract
Understanding how anthropogenic disturbance affects animal behaviour is challenging \nbecause observational studies often involve co-occurring disturbances (e.g., noise, \nlighting, and roadways), and laboratory experiments often lack ecological validity. During \nthe 2016 and 2017 avian breeding seasons, I tested the effects of anthropogenic noise \nand light on the singing and spatial behaviour of birds. I independently manipulated the \npresence of anthropogenic noise and light at 110 sites in an otherwise undisturbed \nboreal forest in Labrador, Canada. Each stimulus was surrounded by a microphone array \nthat recorded and localized singing birds throughout the stimulus presentation. Results \nshow that noise attracts birds, but that light and the interaction between noise and light \nhave little or no effect. None of the treatments affected when birds began singing. My \nstudy provides some of the first experimental evidence of the independent and \ncombined effects of noise and light on the singing and spatial behaviour of wild birds.
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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) | 0.003 | 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".