Seasonal patterns of nocturnal singing by ovenbirds and white-throated sparrows
Bibliographic record
Abstract
Abstract Recent research suggests that many diurnal songbirds also sing at night. The functions of nocturnal singing by diurnally active birds are not well understood. We used automated recorders to record nocturnal singing from May through July 2014. We examined how date, temperature, wind, weather, and lunar phase influenced nocturnal vocal behaviour. We found that nocturnal singing by ovenbirds and white-throated sparrows was related to date with clear seasonal patterns that did not mirror the dawn chorus. Nocturnal singing rates declined seasonally, but peaked earlier for white-throated sparrows than for ovenbirds. Both species sang less often on nights with a full moon or precipitation. Ovenbirds also sang fewer songs on cold and windy nights while white-throated sparrows sang less often on cloudy nights. We show that nocturnal song is shaped by environmental factors and shows a seasonal pattern that may be useful for gaining insights into functions of nocturnal song.
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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 | 0.001 | 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".