Intermittent and chronic noise impacts on hatching success and incubation behavior of Eastern Bluebirds ( Sialia sialis )
Bibliographic record
Abstract
Noise pollution can degrade the behavioral, physiological, and psychological health of humans and other creatures. We used breeding pairs of Eastern Bluebirds (Sialia sialis) to assess behavioral and reproductive responses to both chronic roadway noise and experimental intermittent playbacks of construction noise. Active nests in boxes placed near and far from large roads were randomly assigned as treatments or controls for experimental playbacks during incubation. Using temperature signatures from iButtons placed within nest cups we quantified certain female incubation behaviors (# and length of bouts, # of small temperature fluctuations, and total warming minutes per day) and hatching success was recorded for 40 nests in spring of 2019. Nests in quiet areas that received no additional playback treatments of construction noise had markedly higher nest success than any exposed to noise. Nests exposed to chronic traffic noise only, and quiet nests that received 3–4 days of construction noise had the lowest hatching success. Females in traffic-quiet nests increased restlessness (small temperature fluctuations) and experienced decreasing hatching success as the number of days of construction noise playback increased. Thus, birds choosing either quiet or noisy boxes had contrasting responses to bouts of construction noise. Other female incubation behaviors we could detect were unaffected by noise but changed in expected ways with seasonal progression. In sum, both types of noise can decrease hatch rate, but with intermittent noise this is likely due to female restlessness, or too many small drops in temperature to maintain optimal embryo development.
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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) | 0.001 | 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".